Overview

Dataset statistics

Number of variables328
Number of observations474
Missing cells128451
Missing cells (%)82.6%
Total size in memory6.3 MiB
Average record size in memory13.6 KiB

Variable types

Numeric1
Text238
URL1
Unsupported88

Alerts

priority4_prog2 has constant value ""Constant
priority3_prog3 has constant value ""Constant
priority1_prog6 has constant value ""Constant
priority2_prog6 has constant value ""Constant
priority1_prog7 has constant value ""Constant
priority2_prog7 has constant value ""Constant
priority1_prog8 has constant value ""Constant
priority2_prog8 has constant value ""Constant
admissionsmethod_prog11 has constant value ""Constant
swdseats_prog11 has constant value ""Constant
swdappsperseat_prog11 has constant value ""Constant
gefilled_prog11 has constant value ""Constant
swdfilled_prog11 has constant value ""Constant
code_prog12 has constant value ""Constant
name_prog12 has constant value ""Constant
admissionsmethod_prog12 has constant value ""Constant
geapps_prog12 has constant value ""Constant
swdapps_prog12 has constant value ""Constant
geseats_prog12 has constant value ""Constant
swdseats_prog12 has constant value ""Constant
geappsperseat_prog12 has constant value ""Constant
swdappsperseat_prog12 has constant value ""Constant
gefilled_prog12 has constant value ""Constant
swdfilled_prog12 has constant value ""Constant
eligibility_prog12 has constant value ""Constant
code_prog13 has constant value ""Constant
name_prog13 has constant value ""Constant
admissionsmethod_prog13 has constant value ""Constant
geapps_prog13 has constant value ""Constant
swdapps_prog13 has constant value ""Constant
geseats_prog13 has constant value ""Constant
swdseats_prog13 has constant value ""Constant
geappsperseat_prog13 has constant value ""Constant
swdappsperseat_prog13 has constant value ""Constant
gefilled_prog13 has constant value ""Constant
swdfilled_prog13 has constant value ""Constant
eligibility_prog13 has constant value ""Constant
code_prog14 has constant value ""Constant
name_prog14 has constant value ""Constant
admissionsmethod_prog14 has constant value ""Constant
geapps_prog14 has constant value ""Constant
swdapps_prog14 has constant value ""Constant
geseats_prog14 has constant value ""Constant
swdseats_prog14 has constant value ""Constant
geappsperseat_prog14 has constant value ""Constant
swdappsperseat_prog14 has constant value ""Constant
gefilled_prog14 has constant value ""Constant
swdfilled_prog14 has constant value ""Constant
eligibility_prog14 has constant value ""Constant
code_prog15 has constant value ""Constant
name_prog15 has constant value ""Constant
admissionsmethod_prog15 has constant value ""Constant
geapps_prog15 has constant value ""Constant
swdapps_prog15 has constant value ""Constant
geseats_prog15 has constant value ""Constant
swdseats_prog15 has constant value ""Constant
geappsperseat_prog15 has constant value ""Constant
swdappsperseat_prog15 has constant value ""Constant
gefilled_prog15 has constant value ""Constant
swdfilled_prog15 has constant value ""Constant
eligibility_prog15 has constant value ""Constant
neighborhood has 10 (2.1%) missing valuesMissing
sharedbuilding has 215 (45.4%) missing valuesMissing
independentwebsite has 199 (42.0%) missing valuesMissing
subway has 127 (26.8%) missing valuesMissing
bus has 10 (2.1%) missing valuesMissing
swdappsperseat_prog1 has 19 (4.0%) missing valuesMissing
priority1_prog1 has 190 (40.1%) missing valuesMissing
priority2_prog1 has 191 (40.3%) missing valuesMissing
priority3_prog1 has 371 (78.3%) missing valuesMissing
priority4_prog1 has 460 (97.0%) missing valuesMissing
priority5_prog1 has 474 (100.0%) missing valuesMissing
priority6_prog1 has 474 (100.0%) missing valuesMissing
priority7_prog1 has 474 (100.0%) missing valuesMissing
code_prog2 has 356 (75.1%) missing valuesMissing
name_prog2 has 356 (75.1%) missing valuesMissing
admissionsmethod_prog2 has 356 (75.1%) missing valuesMissing
geapps_prog2 has 357 (75.3%) missing valuesMissing
swdapps_prog2 has 357 (75.3%) missing valuesMissing
geappsperseat_prog2 has 358 (75.5%) missing valuesMissing
swdappsperseat_prog2 has 362 (76.4%) missing valuesMissing
swdseats_prog2 has 357 (75.3%) missing valuesMissing
geseats_prog2 has 357 (75.3%) missing valuesMissing
gefilled_prog2 has 357 (75.3%) missing valuesMissing
swdfilled_prog2 has 357 (75.3%) missing valuesMissing
eligibility_prog2 has 357 (75.3%) missing valuesMissing
priority1_prog2 has 423 (89.2%) missing valuesMissing
priority2_prog2 has 425 (89.7%) missing valuesMissing
priority3_prog2 has 462 (97.5%) missing valuesMissing
priority4_prog2 has 473 (99.8%) missing valuesMissing
priority5_prog2 has 474 (100.0%) missing valuesMissing
priority6_prog2 has 474 (100.0%) missing valuesMissing
priority7_prog2 has 474 (100.0%) missing valuesMissing
code_prog3 has 441 (93.0%) missing valuesMissing
name_prog3 has 441 (93.0%) missing valuesMissing
admissionsmethod_prog3 has 441 (93.0%) missing valuesMissing
geapps_prog3 has 441 (93.0%) missing valuesMissing
swdapps_prog3 has 441 (93.0%) missing valuesMissing
geappsperseat_prog3 has 441 (93.0%) missing valuesMissing
swdappsperseat_prog3 has 441 (93.0%) missing valuesMissing
swdseats_prog3 has 441 (93.0%) missing valuesMissing
geseats_prog3 has 441 (93.0%) missing valuesMissing
gefilled_prog3 has 441 (93.0%) missing valuesMissing
swdfilled_prog3 has 441 (93.0%) missing valuesMissing
eligibility_prog3 has 441 (93.0%) missing valuesMissing
priority1_prog3 has 466 (98.3%) missing valuesMissing
priority2_prog3 has 466 (98.3%) missing valuesMissing
priority3_prog3 has 469 (98.9%) missing valuesMissing
priority4_prog3 has 474 (100.0%) missing valuesMissing
priority5_prog3 has 474 (100.0%) missing valuesMissing
priority6_prog3 has 474 (100.0%) missing valuesMissing
priority7_prog3 has 474 (100.0%) missing valuesMissing
code_prog4 has 464 (97.9%) missing valuesMissing
name_prog4 has 464 (97.9%) missing valuesMissing
admissionsmethod_prog4 has 464 (97.9%) missing valuesMissing
geapps_prog4 has 464 (97.9%) missing valuesMissing
swdapps_prog4 has 464 (97.9%) missing valuesMissing
geappsperseat_prog4 has 464 (97.9%) missing valuesMissing
swdappsperseat_prog4 has 464 (97.9%) missing valuesMissing
swdseats_prog4 has 464 (97.9%) missing valuesMissing
geseats_prog4 has 464 (97.9%) missing valuesMissing
gefilled_prog4 has 464 (97.9%) missing valuesMissing
swdfilled_prog4 has 464 (97.9%) missing valuesMissing
eligibility_prog4 has 464 (97.9%) missing valuesMissing
priority1_prog4 has 474 (100.0%) missing valuesMissing
priority2_prog4 has 474 (100.0%) missing valuesMissing
priority3_prog4 has 474 (100.0%) missing valuesMissing
priority4_prog4 has 474 (100.0%) missing valuesMissing
priority5_prog4 has 474 (100.0%) missing valuesMissing
priority6_prog4 has 474 (100.0%) missing valuesMissing
priority7_prog4 has 474 (100.0%) missing valuesMissing
code_prog5 has 468 (98.7%) missing valuesMissing
name_prog5 has 468 (98.7%) missing valuesMissing
admissionsmethod_prog5 has 468 (98.7%) missing valuesMissing
geapps_prog5 has 468 (98.7%) missing valuesMissing
swdapps_prog5 has 468 (98.7%) missing valuesMissing
geappsperseat_prog5 has 468 (98.7%) missing valuesMissing
swdappsperseat_prog5 has 468 (98.7%) missing valuesMissing
swdseats_prog5 has 468 (98.7%) missing valuesMissing
geseats_prog5 has 468 (98.7%) missing valuesMissing
gefilled_prog5 has 468 (98.7%) missing valuesMissing
swdfilled_prog5 has 468 (98.7%) missing valuesMissing
eligibility_prog5 has 468 (98.7%) missing valuesMissing
priority1_prog5 has 474 (100.0%) missing valuesMissing
priority2_prog5 has 474 (100.0%) missing valuesMissing
priority3_prog5 has 474 (100.0%) missing valuesMissing
priority4_prog5 has 474 (100.0%) missing valuesMissing
priority5_prog5 has 474 (100.0%) missing valuesMissing
priority6_prog5 has 474 (100.0%) missing valuesMissing
priority7_prog5 has 474 (100.0%) missing valuesMissing
code_prog6 has 468 (98.7%) missing valuesMissing
name_prog6 has 468 (98.7%) missing valuesMissing
admissionsmethod_prog6 has 468 (98.7%) missing valuesMissing
geapps_prog6 has 468 (98.7%) missing valuesMissing
swdapps_prog6 has 468 (98.7%) missing valuesMissing
geappsperseat_prog6 has 468 (98.7%) missing valuesMissing
swdappsperseat_prog6 has 468 (98.7%) missing valuesMissing
swdseats_prog6 has 468 (98.7%) missing valuesMissing
geseats_prog6 has 468 (98.7%) missing valuesMissing
gefilled_prog6 has 468 (98.7%) missing valuesMissing
swdfilled_prog6 has 468 (98.7%) missing valuesMissing
eligibility_prog6 has 468 (98.7%) missing valuesMissing
priority1_prog6 has 473 (99.8%) missing valuesMissing
priority2_prog6 has 473 (99.8%) missing valuesMissing
priority3_prog6 has 474 (100.0%) missing valuesMissing
priority4_prog6 has 474 (100.0%) missing valuesMissing
priority5_prog6 has 474 (100.0%) missing valuesMissing
priority6_prog6 has 474 (100.0%) missing valuesMissing
priority7_prog6 has 474 (100.0%) missing valuesMissing
code_prog7 has 468 (98.7%) missing valuesMissing
name_prog7 has 468 (98.7%) missing valuesMissing
admissionsmethod_prog7 has 468 (98.7%) missing valuesMissing
geapps_prog7 has 468 (98.7%) missing valuesMissing
swdapps_prog7 has 468 (98.7%) missing valuesMissing
geseats_prog7 has 468 (98.7%) missing valuesMissing
swdseats_prog7 has 468 (98.7%) missing valuesMissing
geappsperseat_prog7 has 468 (98.7%) missing valuesMissing
swdappsperseat_prog7 has 468 (98.7%) missing valuesMissing
gefilled_prog7 has 468 (98.7%) missing valuesMissing
swdfilled_prog7 has 468 (98.7%) missing valuesMissing
eligibility_prog7 has 468 (98.7%) missing valuesMissing
priority1_prog7 has 473 (99.8%) missing valuesMissing
priority2_prog7 has 473 (99.8%) missing valuesMissing
priority3_prog7 has 474 (100.0%) missing valuesMissing
priority4_prog7 has 474 (100.0%) missing valuesMissing
priority5_prog7 has 474 (100.0%) missing valuesMissing
priority6_prog7 has 474 (100.0%) missing valuesMissing
priority7_prog7 has 474 (100.0%) missing valuesMissing
code_prog8 has 469 (98.9%) missing valuesMissing
name_prog8 has 469 (98.9%) missing valuesMissing
admissionsmethod_prog8 has 469 (98.9%) missing valuesMissing
geapps_prog8 has 469 (98.9%) missing valuesMissing
swdapps_prog8 has 469 (98.9%) missing valuesMissing
geseats_prog8 has 469 (98.9%) missing valuesMissing
swdseats_prog8 has 469 (98.9%) missing valuesMissing
geappsperseat_prog8 has 469 (98.9%) missing valuesMissing
swdappsperseat_prog8 has 469 (98.9%) missing valuesMissing
gefilled_prog8 has 469 (98.9%) missing valuesMissing
swdfilled_prog8 has 469 (98.9%) missing valuesMissing
eligibility_prog8 has 469 (98.9%) missing valuesMissing
priority1_prog8 has 473 (99.8%) missing valuesMissing
priority2_prog8 has 473 (99.8%) missing valuesMissing
priority3_prog8 has 474 (100.0%) missing valuesMissing
priority4_prog8 has 474 (100.0%) missing valuesMissing
priority5_prog8 has 474 (100.0%) missing valuesMissing
priority6_prog8 has 474 (100.0%) missing valuesMissing
priority7_prog8 has 474 (100.0%) missing valuesMissing
code_prog9 has 470 (99.2%) missing valuesMissing
name_prog9 has 470 (99.2%) missing valuesMissing
admissionsmethod_prog9 has 470 (99.2%) missing valuesMissing
geapps_prog9 has 470 (99.2%) missing valuesMissing
swdapps_prog9 has 470 (99.2%) missing valuesMissing
geseats_prog9 has 470 (99.2%) missing valuesMissing
swdseats_prog9 has 470 (99.2%) missing valuesMissing
geappsperseat_prog9 has 470 (99.2%) missing valuesMissing
swdappsperseat_prog9 has 470 (99.2%) missing valuesMissing
gefilled_prog9 has 470 (99.2%) missing valuesMissing
swdfilled_prog9 has 470 (99.2%) missing valuesMissing
eligibility_prog9 has 470 (99.2%) missing valuesMissing
priority1_prog9 has 474 (100.0%) missing valuesMissing
priority2_prog9 has 474 (100.0%) missing valuesMissing
priority3_prog9 has 474 (100.0%) missing valuesMissing
priority4_prog9 has 474 (100.0%) missing valuesMissing
priority5_prog9 has 474 (100.0%) missing valuesMissing
priority6_prog9 has 474 (100.0%) missing valuesMissing
priority7_prog9 has 474 (100.0%) missing valuesMissing
code_prog10 has 471 (99.4%) missing valuesMissing
name_prog10 has 471 (99.4%) missing valuesMissing
admissionsmethod_prog10 has 471 (99.4%) missing valuesMissing
geapps_prog10 has 471 (99.4%) missing valuesMissing
swdapps_prog10 has 471 (99.4%) missing valuesMissing
geseats_prog10 has 471 (99.4%) missing valuesMissing
swdseats_prog10 has 471 (99.4%) missing valuesMissing
geappsperseat_prog10 has 472 (99.6%) missing valuesMissing
swdappsperseat_prog10 has 472 (99.6%) missing valuesMissing
gefilled_prog10 has 471 (99.4%) missing valuesMissing
swdfilled_prog10 has 471 (99.4%) missing valuesMissing
eligibility_prog10 has 471 (99.4%) missing valuesMissing
priority1_prog10 has 474 (100.0%) missing valuesMissing
priority2_prog10 has 474 (100.0%) missing valuesMissing
priority3_prog10 has 474 (100.0%) missing valuesMissing
priority4_prog10 has 474 (100.0%) missing valuesMissing
priority5_prog10 has 474 (100.0%) missing valuesMissing
priority6_prog10 has 474 (100.0%) missing valuesMissing
priority7_prog10 has 474 (100.0%) missing valuesMissing
code_prog11 has 472 (99.6%) missing valuesMissing
name_prog11 has 472 (99.6%) missing valuesMissing
admissionsmethod_prog11 has 472 (99.6%) missing valuesMissing
geapps_prog11 has 472 (99.6%) missing valuesMissing
swdapps_prog11 has 472 (99.6%) missing valuesMissing
geseats_prog11 has 472 (99.6%) missing valuesMissing
swdseats_prog11 has 472 (99.6%) missing valuesMissing
geappsperseat_prog11 has 472 (99.6%) missing valuesMissing
swdappsperseat_prog11 has 472 (99.6%) missing valuesMissing
gefilled_prog11 has 472 (99.6%) missing valuesMissing
swdfilled_prog11 has 472 (99.6%) missing valuesMissing
eligibility_prog11 has 472 (99.6%) missing valuesMissing
priority1_prog11 has 474 (100.0%) missing valuesMissing
priority2_prog11 has 474 (100.0%) missing valuesMissing
priority3_prog11 has 474 (100.0%) missing valuesMissing
priority4_prog11 has 474 (100.0%) missing valuesMissing
priority5_prog11 has 474 (100.0%) missing valuesMissing
priority6_prog11 has 474 (100.0%) missing valuesMissing
priority7_prog11 has 474 (100.0%) missing valuesMissing
code_prog12 has 473 (99.8%) missing valuesMissing
name_prog12 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog12 has 473 (99.8%) missing valuesMissing
geapps_prog12 has 473 (99.8%) missing valuesMissing
swdapps_prog12 has 473 (99.8%) missing valuesMissing
geseats_prog12 has 473 (99.8%) missing valuesMissing
swdseats_prog12 has 473 (99.8%) missing valuesMissing
geappsperseat_prog12 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog12 has 473 (99.8%) missing valuesMissing
gefilled_prog12 has 473 (99.8%) missing valuesMissing
swdfilled_prog12 has 473 (99.8%) missing valuesMissing
eligibility_prog12 has 473 (99.8%) missing valuesMissing
priority1_prog12 has 474 (100.0%) missing valuesMissing
priority2_prog12 has 474 (100.0%) missing valuesMissing
priority3_prog12 has 474 (100.0%) missing valuesMissing
priority4_prog12 has 474 (100.0%) missing valuesMissing
priority5_prog12 has 474 (100.0%) missing valuesMissing
priority6_prog12 has 474 (100.0%) missing valuesMissing
priority7_prog12 has 474 (100.0%) missing valuesMissing
code_prog13 has 473 (99.8%) missing valuesMissing
name_prog13 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog13 has 473 (99.8%) missing valuesMissing
geapps_prog13 has 473 (99.8%) missing valuesMissing
swdapps_prog13 has 473 (99.8%) missing valuesMissing
geseats_prog13 has 473 (99.8%) missing valuesMissing
swdseats_prog13 has 473 (99.8%) missing valuesMissing
geappsperseat_prog13 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog13 has 473 (99.8%) missing valuesMissing
gefilled_prog13 has 473 (99.8%) missing valuesMissing
swdfilled_prog13 has 473 (99.8%) missing valuesMissing
eligibility_prog13 has 473 (99.8%) missing valuesMissing
priority1_prog13 has 474 (100.0%) missing valuesMissing
priority2_prog13 has 474 (100.0%) missing valuesMissing
priority3_prog13 has 474 (100.0%) missing valuesMissing
priority4_prog13 has 474 (100.0%) missing valuesMissing
priority5_prog13 has 474 (100.0%) missing valuesMissing
priority6_prog13 has 474 (100.0%) missing valuesMissing
priority7_prog13 has 474 (100.0%) missing valuesMissing
code_prog14 has 473 (99.8%) missing valuesMissing
name_prog14 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog14 has 473 (99.8%) missing valuesMissing
geapps_prog14 has 473 (99.8%) missing valuesMissing
swdapps_prog14 has 473 (99.8%) missing valuesMissing
geseats_prog14 has 473 (99.8%) missing valuesMissing
swdseats_prog14 has 473 (99.8%) missing valuesMissing
geappsperseat_prog14 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog14 has 473 (99.8%) missing valuesMissing
gefilled_prog14 has 473 (99.8%) missing valuesMissing
swdfilled_prog14 has 473 (99.8%) missing valuesMissing
eligibility_prog14 has 473 (99.8%) missing valuesMissing
priority1_prog14 has 474 (100.0%) missing valuesMissing
priority2_prog14 has 474 (100.0%) missing valuesMissing
priority3_prog14 has 474 (100.0%) missing valuesMissing
priority4_prog14 has 474 (100.0%) missing valuesMissing
priority5_prog14 has 474 (100.0%) missing valuesMissing
priority6_prog14 has 474 (100.0%) missing valuesMissing
priority7_prog14 has 474 (100.0%) missing valuesMissing
code_prog15 has 473 (99.8%) missing valuesMissing
name_prog15 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog15 has 473 (99.8%) missing valuesMissing
geapps_prog15 has 473 (99.8%) missing valuesMissing
swdapps_prog15 has 473 (99.8%) missing valuesMissing
geseats_prog15 has 473 (99.8%) missing valuesMissing
swdseats_prog15 has 473 (99.8%) missing valuesMissing
geappsperseat_prog15 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog15 has 473 (99.8%) missing valuesMissing
gefilled_prog15 has 473 (99.8%) missing valuesMissing
swdfilled_prog15 has 473 (99.8%) missing valuesMissing
eligibility_prog15 has 473 (99.8%) missing valuesMissing
priority1_prog15 has 474 (100.0%) missing valuesMissing
priority2_prog15 has 474 (100.0%) missing valuesMissing
priority3_prog15 has 474 (100.0%) missing valuesMissing
priority4_prog15 has 474 (100.0%) missing valuesMissing
priority5_prog15 has 474 (100.0%) missing valuesMissing
priority6_prog15 has 474 (100.0%) missing valuesMissing
priority7_prog15 has 474 (100.0%) missing valuesMissing
coursepassrate has 6 (1.3%) missing valuesMissing
elaprof has 6 (1.3%) missing valuesMissing
mathprof has 6 (1.3%) missing valuesMissing
tophs1 has 13 (2.7%) missing valuesMissing
tophs2 has 106 (22.4%) missing valuesMissing
tophs3 has 260 (54.9%) missing valuesMissing
surveysafety has 6 (1.3%) missing valuesMissing
diversityinadmissions has 442 (93.2%) missing valuesMissing
start_time has 11 (2.3%) missing valuesMissing
end_time has 13 (2.7%) missing valuesMissing
other_features has 177 (37.3%) missing valuesMissing
languageclasses has 105 (22.2%) missing valuesMissing
acceleratedclasses has 88 (18.6%) missing valuesMissing
electiveclasses has 118 (24.9%) missing valuesMissing
activities_description has 119 (25.1%) missing valuesMissing
othersports has 121 (25.5%) missing valuesMissing
0 has unique valuesUnique
schooldbn has unique valuesUnique
name has unique valuesUnique
url has unique valuesUnique
code_prog1 has unique valuesUnique
priority5_prog1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 22:46:38.877434
Analysis finished2023-12-09 22:46:47.465956
Duration8.59 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean237.5
Minimum1
Maximum474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-09T22:46:48.097625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24.65
Q1119.25
median237.5
Q3355.75
95-th percentile450.35
Maximum474
Range473
Interquartile range (IQR)236.5

Descriptive statistics

Standard deviation136.9762753
Coefficient of variation (CV)0.5767422119
Kurtosis-1.2
Mean237.5
Median Absolute Deviation (MAD)118.5
Skewness0
Sum112575
Variance18762.5
MonotonicityStrictly increasing
2023-12-09T22:46:48.279208image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
312 1
 
0.2%
324 1
 
0.2%
323 1
 
0.2%
322 1
 
0.2%
321 1
 
0.2%
320 1
 
0.2%
319 1
 
0.2%
318 1
 
0.2%
317 1
 
0.2%
Other values (464) 464
97.9%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
ValueCountFrequency (%)
474 1
0.2%
473 1
0.2%
472 1
0.2%
471 1
0.2%
470 1
0.2%

district
Text

Distinct32
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2023-12-09T22:46:48.766249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.685654008
Min length1

Characters and Unicode

Total characters799
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
10 27
 
5.7%
9 25
 
5.3%
2 23
 
4.9%
27 23
 
4.9%
11 20
 
4.2%
3 19
 
4.0%
6 19
 
4.0%
29 17
 
3.6%
19 17
 
3.6%
8 16
 
3.4%
Other values (22) 268
56.5%
2023-12-09T22:46:49.145567image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 201
25.2%
2 201
25.2%
3 82
10.3%
0 59
 
7.4%
9 59
 
7.4%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 799
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 201
25.2%
2 201
25.2%
3 82
10.3%
0 59
 
7.4%
9 59
 
7.4%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 799
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 201
25.2%
2 201
25.2%
3 82
10.3%
0 59
 
7.4%
9 59
 
7.4%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 799
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 201
25.2%
2 201
25.2%
3 82
10.3%
0 59
 
7.4%
9 59
 
7.4%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

schooldbn
Text

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size29.3 KiB
2023-12-09T22:46:49.606485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2844
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)100.0%

Sample

1st row01M034
2nd row01M140
3rd row01M184
4th row01M188
5th row01M332
ValueCountFrequency (%)
30q204 1
 
0.2%
02m217 1
 
0.2%
21k228 1
 
0.2%
07x029 1
 
0.2%
31r072 1
 
0.2%
09x218 1
 
0.2%
30q580 1
 
0.2%
27q232 1
 
0.2%
04m206 1
 
0.2%
30q126 1
 
0.2%
Other values (464) 464
97.9%
2023-12-09T22:46:50.170104image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 428
15.0%
1 394
13.9%
0 378
13.3%
3 252
8.9%
4 167
 
5.9%
8 162
 
5.7%
9 154
 
5.4%
7 148
 
5.2%
6 144
 
5.1%
5 143
 
5.0%
Other values (5) 474
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2370
83.3%
Uppercase Letter 474
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 428
18.1%
1 394
16.6%
0 378
15.9%
3 252
10.6%
4 167
 
7.0%
8 162
 
6.8%
9 154
 
6.5%
7 148
 
6.2%
6 144
 
6.1%
5 143
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
K 143
30.2%
X 116
24.5%
Q 105
22.2%
M 95
20.0%
R 15
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2370
83.3%
Latin 474
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 428
18.1%
1 394
16.6%
0 378
15.9%
3 252
10.6%
4 167
 
7.0%
8 162
 
6.8%
9 154
 
6.5%
7 148
 
6.2%
6 144
 
6.1%
5 143
 
6.0%
Latin
ValueCountFrequency (%)
K 143
30.2%
X 116
24.5%
Q 105
22.2%
M 95
20.0%
R 15
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 428
15.0%
1 394
13.9%
0 378
13.3%
3 252
8.9%
4 167
 
5.9%
8 162
 
5.7%
9 154
 
5.4%
7 148
 
5.2%
6 144
 
5.1%
5 143
 
5.0%
Other values (5) 474
16.7%

name
Text

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size39.9 KiB
2023-12-09T22:46:50.517678image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length78
Median length55.5
Mean length28.91772152
Min length5

Characters and Unicode

Total characters13707
Distinct characters73
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)100.0%

Sample

1st rowP.S. 034 Franklin D. Roosevelt
2nd rowP.S. 140 Nathan Straus
3rd rowP.S. 184m Shuang Wen
4th rowP.S. 188 The Island School
5th rowUniversity Neighborhood Middle School
ValueCountFrequency (%)
school 178
 
8.0%
p.s 74
 
3.3%
academy 72
 
3.2%
the 69
 
3.1%
i.s 63
 
2.8%
middle 55
 
2.5%
for 55
 
2.5%
j.h.s 43
 
1.9%
of 40
 
1.8%
m.s 36
 
1.6%
Other values (868) 1543
69.3%
2023-12-09T22:46:51.031404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1754
 
12.8%
e 984
 
7.2%
o 948
 
6.9%
a 698
 
5.1%
. 667
 
4.9%
l 643
 
4.7%
r 590
 
4.3%
S 572
 
4.2%
n 563
 
4.1%
i 491
 
3.6%
Other values (63) 5797
42.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8198
59.8%
Uppercase Letter 2227
 
16.2%
Space Separator 1754
 
12.8%
Other Punctuation 754
 
5.5%
Decimal Number 754
 
5.5%
Dash Punctuation 18
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 984
12.0%
o 948
11.6%
a 698
 
8.5%
l 643
 
7.8%
r 590
 
7.2%
n 563
 
6.9%
i 491
 
6.0%
c 444
 
5.4%
h 420
 
5.1%
t 407
 
5.0%
Other values (16) 2010
24.5%
Uppercase Letter
ValueCountFrequency (%)
S 572
25.7%
M 202
 
9.1%
P 181
 
8.1%
A 171
 
7.7%
I 140
 
6.3%
C 110
 
4.9%
H 107
 
4.8%
T 96
 
4.3%
B 84
 
3.8%
J 81
 
3.6%
Other values (16) 483
21.7%
Decimal Number
ValueCountFrequency (%)
1 134
17.8%
2 122
16.2%
0 112
14.9%
3 75
9.9%
8 66
8.8%
4 57
7.6%
9 52
 
6.9%
7 52
 
6.9%
5 47
 
6.2%
6 37
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 667
88.5%
/ 37
 
4.9%
& 17
 
2.3%
, 15
 
2.0%
: 10
 
1.3%
' 7
 
0.9%
\ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1754
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10425
76.1%
Common 3282
 
23.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 984
 
9.4%
o 948
 
9.1%
a 698
 
6.7%
l 643
 
6.2%
r 590
 
5.7%
S 572
 
5.5%
n 563
 
5.4%
i 491
 
4.7%
c 444
 
4.3%
h 420
 
4.0%
Other values (42) 4072
39.1%
Common
ValueCountFrequency (%)
1754
53.4%
. 667
 
20.3%
1 134
 
4.1%
2 122
 
3.7%
0 112
 
3.4%
3 75
 
2.3%
8 66
 
2.0%
4 57
 
1.7%
9 52
 
1.6%
7 52
 
1.6%
Other values (11) 191
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13707
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1754
 
12.8%
e 984
 
7.2%
o 948
 
6.9%
a 698
 
5.1%
. 667
 
4.9%
l 643
 
4.7%
r 590
 
4.3%
S 572
 
4.2%
n 563
 
4.1%
i 491
 
3.6%
Other values (63) 5797
42.3%

overview
Text

Distinct473
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size438.1 KiB
2023-12-09T22:46:51.422486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1816
Median length1036
Mean length890.2325581
Min length12

Characters and Unicode

Total characters421080
Distinct characters99
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique473 ?
Unique (%)100.0%

Sample

1st rowMock Trial; Restorative Practices; Student Centered Learning; MSQI
2nd rowPS/MS 140M is committed to creating a community of learners who have the opportunity to develop their character and intellect through project-based learning that encourages collaboration, inquiry and critical thinking. Learners will engage in real-world application of their understandings. We will be part of a respectful, inclusive learning environment, providing equity in our diverse learning community across all disciplines, making our students become leaders, change makers, active citizens and empowered members of our community. We have a quality Arts program which include dance, music/choral, and visual arts. M140 has many partnerships, such as Educational Alliance, Henry Street Mental Health Clinic, Rosie's Broadway Kids, Artist Space, Marquise Studios, Champs, ThriveNYC, NY Cares and Asphalt Green.
3rd rowShuang Wen has received honors including NYSED Recognition School (2018-19), U.S. Blue Ribbon School (since 2013), and NYS Reward School (since 2013). We have school-wide Chinese-English Dual Language Classes and ICT classes from K-8. We also have our After School Program, Monday-Friday, 2:40-5:00 p.m.
4th rowOur mission at the Island School is to be relentless in our pursuit of best practices to support student success. One way that we have done that—and will continue to do it—is by giving students a wide array of experiences so that they can identify areas of interest and talent and then develop those interests and talents into lifelong passions. Our faculty is committed to helping each of our children reach their full academic potential. We are developing a culture of college-minded students and working with community members to create a challenging learning environment. As a Community School, we look at how we can support the whole child. We provide services not only for our children but for our families. Parents like that we help identify and nurture their children's interest as well as their own talents. Parents appreciate our partnerships with high schools such as Bard High School Early College and Orchard Collegiate High School.
5th rowSomething that makes UNMS so special is the goal we share in providing a nurturing and valuable school experience for our children. We believe that education plays a crucial role in the successful academic, emotional, and physical development of every child. Our learning community inspires our students because we have an amazing group of educators who instill a passion for learning and a commitment to make a difference. UNMS is committed to work relentlessly to support a learning environment where each child is cared for, valued and seen. We are committed to providing opportunities that promote collaboration between our UNMS community members because we know it takes a village to teach the whole child. Together we make the difference!
ValueCountFrequency (%)
and 3344
 
5.3%
the 2117
 
3.3%
to 1967
 
3.1%
our 1504
 
2.4%
students 1497
 
2.4%
a 1471
 
2.3%
in 1372
 
2.2%
of 1335
 
2.1%
school 1256
 
2.0%
we 1012
 
1.6%
Other values (5376) 46512
73.4%
2023-12-09T22:46:51.996895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63655
15.1%
e 39000
 
9.3%
t 28064
 
6.7%
a 26596
 
6.3%
o 25520
 
6.1%
n 24719
 
5.9%
i 24236
 
5.8%
r 23107
 
5.5%
s 22721
 
5.4%
l 16159
 
3.8%
Other values (89) 127303
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 330289
78.4%
Space Separator 63670
 
15.1%
Uppercase Letter 14151
 
3.4%
Other Punctuation 9212
 
2.2%
Decimal Number 2024
 
0.5%
Dash Punctuation 1057
 
0.3%
Close Punctuation 227
 
0.1%
Open Punctuation 226
 
0.1%
Control 208
 
< 0.1%
Currency Symbol 12
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 2147
15.2%
A 1414
 
10.0%
C 1028
 
7.3%
T 930
 
6.6%
W 888
 
6.3%
M 861
 
6.1%
P 780
 
5.5%
E 777
 
5.5%
O 622
 
4.4%
I 586
 
4.1%
Other values (18) 4118
29.1%
Lowercase Letter
ValueCountFrequency (%)
e 39000
11.8%
t 28064
 
8.5%
a 26596
 
8.1%
o 25520
 
7.7%
n 24719
 
7.5%
i 24236
 
7.3%
r 23107
 
7.0%
s 22721
 
6.9%
l 16159
 
4.9%
c 14461
 
4.4%
Other values (17) 85706
25.9%
Other Punctuation
ValueCountFrequency (%)
, 4522
49.1%
. 3548
38.5%
' 297
 
3.2%
: 186
 
2.0%
" 170
 
1.8%
/ 166
 
1.8%
; 127
 
1.4%
! 83
 
0.9%
& 66
 
0.7%
% 30
 
0.3%
Other values (5) 17
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 389
19.2%
2 350
17.3%
0 263
13.0%
8 245
12.1%
3 180
8.9%
6 150
 
7.4%
7 120
 
5.9%
9 116
 
5.7%
5 116
 
5.7%
4 95
 
4.7%
Control
ValueCountFrequency (%)
‚ 98
47.1%
ƒ 66
31.7%
13
 
6.2%
€ 13
 
6.2%
” 7
 
3.4%
™ 5
 
2.4%
‘ 2
 
1.0%
“ 2
 
1.0%
Â’ 1
 
0.5%
œ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
63655
> 99.9%
  15
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 224
98.7%
] 3
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 223
98.7%
[ 3
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 1057
100.0%
Currency Symbol
ValueCountFrequency (%)
¢ 12
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 344440
81.8%
Common 76640
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 39000
 
11.3%
t 28064
 
8.1%
a 26596
 
7.7%
o 25520
 
7.4%
n 24719
 
7.2%
i 24236
 
7.0%
r 23107
 
6.7%
s 22721
 
6.6%
l 16159
 
4.7%
c 14461
 
4.2%
Other values (45) 99857
29.0%
Common
ValueCountFrequency (%)
63655
83.1%
, 4522
 
5.9%
. 3548
 
4.6%
- 1057
 
1.4%
1 389
 
0.5%
2 350
 
0.5%
' 297
 
0.4%
0 263
 
0.3%
8 245
 
0.3%
) 224
 
0.3%
Other values (34) 2090
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420637
99.9%
None 443
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63655
15.1%
e 39000
 
9.3%
t 28064
 
6.7%
a 26596
 
6.3%
o 25520
 
6.1%
n 24719
 
5.9%
i 24236
 
5.8%
r 23107
 
5.5%
s 22721
 
5.4%
l 16159
 
3.8%
Other values (75) 126860
30.2%
None
ValueCountFrequency (%)
 110
24.8%
à 110
24.8%
‚ 98
22.1%
ƒ 66
14.9%
  15
 
3.4%
€ 13
 
2.9%
¢ 12
 
2.7%
” 7
 
1.6%
™ 5
 
1.1%
‘ 2
 
0.5%
Other values (4) 5
 
1.1%

neighborhood
Text

MISSING 

Distinct150
Distinct (%)32.3%
Missing10
Missing (%)2.1%
Memory size31.4 KiB
2023-12-09T22:46:52.317099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length17
Mean length11.40301724
Min length5

Characters and Unicode

Total characters5291
Distinct characters51
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)10.8%

Sample

1st rowEast Village
2nd rowLower East Side
3rd rowLower East Side
4th rowEast Village
5th rowLower East Side
ValueCountFrequency (%)
east 61
 
7.7%
heights 36
 
4.6%
park 29
 
3.7%
side 24
 
3.0%
harlem 22
 
2.8%
upper 18
 
2.3%
west 17
 
2.2%
south 17
 
2.2%
york 15
 
1.9%
new 15
 
1.9%
Other values (157) 534
67.8%
2023-12-09T22:46:52.778148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 460
 
8.7%
a 412
 
7.8%
r 372
 
7.0%
o 339
 
6.4%
s 339
 
6.4%
t 335
 
6.3%
324
 
6.1%
i 291
 
5.5%
n 281
 
5.3%
l 252
 
4.8%
Other values (41) 1886
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4170
78.8%
Uppercase Letter 791
 
14.9%
Space Separator 324
 
6.1%
Dash Punctuation 4
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 460
11.0%
a 412
9.9%
r 372
 
8.9%
o 339
 
8.1%
s 339
 
8.1%
t 335
 
8.0%
i 291
 
7.0%
n 281
 
6.7%
l 252
 
6.0%
h 153
 
3.7%
Other values (14) 936
22.4%
Uppercase Letter
ValueCountFrequency (%)
H 105
13.3%
B 85
10.7%
S 72
 
9.1%
E 70
 
8.8%
W 47
 
5.9%
C 46
 
5.8%
P 44
 
5.6%
F 41
 
5.2%
M 41
 
5.2%
G 36
 
4.6%
Other values (14) 204
25.8%
Space Separator
ValueCountFrequency (%)
324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4961
93.8%
Common 330
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 460
 
9.3%
a 412
 
8.3%
r 372
 
7.5%
o 339
 
6.8%
s 339
 
6.8%
t 335
 
6.8%
i 291
 
5.9%
n 281
 
5.7%
l 252
 
5.1%
h 153
 
3.1%
Other values (38) 1727
34.8%
Common
ValueCountFrequency (%)
324
98.2%
- 4
 
1.2%
. 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 460
 
8.7%
a 412
 
7.8%
r 372
 
7.0%
o 339
 
6.4%
s 339
 
6.4%
t 335
 
6.3%
324
 
6.1%
i 291
 
5.5%
n 281
 
5.3%
l 252
 
4.8%
Other values (41) 1886
35.6%

address
Text

Distinct415
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size43.9 KiB
2023-12-09T22:46:53.177010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length45
Mean length37.46835443
Min length30

Characters and Unicode

Total characters17760
Distinct characters61
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique362 ?
Unique (%)76.4%

Sample

1st row730 East 12 Street, New York, NY 10009
2nd row123 Ridge Street, New York, NY 10002
3rd row327 Cherry Street, New York, NY 10002
4th row442 East Houston Street, New York, NY 10002
5th row220 Henry Street, New York, NY 10002
ValueCountFrequency (%)
ny 474
 
15.3%
street 206
 
6.7%
avenue 189
 
6.1%
brooklyn 143
 
4.6%
bronx 116
 
3.8%
queens 102
 
3.3%
york 100
 
3.2%
new 99
 
3.2%
east 55
 
1.8%
west 45
 
1.5%
Other values (848) 1562
50.5%
2023-12-09T22:46:53.706981image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2650
 
14.9%
e 1445
 
8.1%
1 1264
 
7.1%
, 947
 
5.3%
0 796
 
4.5%
r 772
 
4.3%
n 735
 
4.1%
o 705
 
4.0%
t 689
 
3.9%
N 587
 
3.3%
Other values (51) 7170
40.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7129
40.1%
Decimal Number 4457
25.1%
Space Separator 2650
 
14.9%
Uppercase Letter 2474
 
13.9%
Other Punctuation 949
 
5.3%
Dash Punctuation 101
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1445
20.3%
r 772
10.8%
n 735
10.3%
o 705
9.9%
t 689
9.7%
u 354
 
5.0%
a 339
 
4.8%
s 306
 
4.3%
l 289
 
4.1%
k 281
 
3.9%
Other values (14) 1214
17.0%
Uppercase Letter
ValueCountFrequency (%)
N 587
23.7%
Y 574
23.2%
B 322
13.0%
S 257
10.4%
A 206
 
8.3%
Q 103
 
4.2%
W 72
 
2.9%
E 62
 
2.5%
R 43
 
1.7%
P 41
 
1.7%
Other values (13) 207
 
8.4%
Decimal Number
ValueCountFrequency (%)
1 1264
28.4%
0 796
17.9%
2 527
11.8%
4 386
 
8.7%
3 363
 
8.1%
5 350
 
7.9%
6 250
 
5.6%
7 215
 
4.8%
8 162
 
3.6%
9 144
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 947
99.8%
' 2
 
0.2%
Space Separator
ValueCountFrequency (%)
2650
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9603
54.1%
Common 8157
45.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1445
15.0%
r 772
 
8.0%
n 735
 
7.7%
o 705
 
7.3%
t 689
 
7.2%
N 587
 
6.1%
Y 574
 
6.0%
u 354
 
3.7%
a 339
 
3.5%
B 322
 
3.4%
Other values (37) 3081
32.1%
Common
ValueCountFrequency (%)
2650
32.5%
1 1264
15.5%
, 947
 
11.6%
0 796
 
9.8%
2 527
 
6.5%
4 386
 
4.7%
3 363
 
4.5%
5 350
 
4.3%
6 250
 
3.1%
7 215
 
2.6%
Other values (4) 409
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2650
 
14.9%
e 1445
 
8.1%
1 1264
 
7.1%
, 947
 
5.3%
0 796
 
4.5%
r 772
 
4.3%
n 735
 
4.1%
o 705
 
4.0%
t 689
 
3.9%
N 587
 
3.3%
Other values (51) 7170
40.4%

sharedbuilding
Text

MISSING 

Distinct221
Distinct (%)85.3%
Missing215
Missing (%)45.4%
Memory size23.9 KiB
2023-12-09T22:46:54.045392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length10
Mean length10.26254826
Min length10

Characters and Unicode

Total characters2658
Distinct characters21
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)72.6%

Sample

1st rowYes-01M137
2nd rowYes-01M056
3rd rowYes-01M025
4th rowYes-01M060
5th rowYes-01M022
ValueCountFrequency (%)
yes-03m118 3
 
1.1%
yes-11x142 3
 
1.1%
yes-09x145 3
 
1.1%
yes-03m044 3
 
1.1%
yes-11x135 3
 
1.1%
yes-12x116 2
 
0.8%
yes-09x147 2
 
0.8%
yes-06m090 2
 
0.8%
yes-12x193 2
 
0.8%
yes-17k465 2
 
0.8%
Other values (214) 237
90.5%
2023-12-09T22:46:54.507397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 259
9.7%
s 259
9.7%
- 259
9.7%
e 259
9.7%
1 255
9.6%
0 245
9.2%
2 182
 
6.8%
3 133
 
5.0%
4 101
 
3.8%
9 96
 
3.6%
Other values (11) 610
22.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1341
50.5%
Uppercase Letter 526
 
19.8%
Lowercase Letter 518
 
19.5%
Dash Punctuation 259
 
9.7%
Other Punctuation 11
 
0.4%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 255
19.0%
0 245
18.3%
2 182
13.6%
3 133
9.9%
4 101
 
7.5%
9 96
 
7.2%
8 89
 
6.6%
6 84
 
6.3%
5 79
 
5.9%
7 77
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
Y 259
49.2%
X 79
 
15.0%
K 73
 
13.9%
M 69
 
13.1%
Q 41
 
7.8%
R 5
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
s 259
50.0%
e 259
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 259
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1614
60.7%
Latin 1044
39.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 259
16.0%
1 255
15.8%
0 245
15.2%
2 182
11.3%
3 133
8.2%
4 101
 
6.3%
9 96
 
5.9%
8 89
 
5.5%
6 84
 
5.2%
5 79
 
4.9%
Other values (3) 91
 
5.6%
Latin
ValueCountFrequency (%)
Y 259
24.8%
s 259
24.8%
e 259
24.8%
X 79
 
7.6%
K 73
 
7.0%
M 69
 
6.6%
Q 41
 
3.9%
R 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 259
9.7%
s 259
9.7%
- 259
9.7%
e 259
9.7%
1 255
9.6%
0 245
9.2%
2 182
 
6.8%
3 133
 
5.0%
4 101
 
3.8%
9 96
 
3.6%
Other values (11) 610
22.9%

accessibility_description
Text

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size34.1 KiB
2023-12-09T22:46:54.682840image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length20
Median length16
Mean length16.48945148
Min length14

Characters and Unicode

Total characters7816
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Accessible
2nd rowNot Accessible
3rd rowPartially Accessible
4th rowFully Accessible
5th rowPartially Accessible
ValueCountFrequency (%)
accessible 474
50.0%
not 192
20.3%
partially 154
 
16.2%
fully 128
 
13.5%
2023-12-09T22:46:54.962749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1038
13.3%
c 948
12.1%
e 948
12.1%
s 948
12.1%
i 628
8.0%
474
 
6.1%
A 474
 
6.1%
b 474
 
6.1%
t 346
 
4.4%
a 308
 
3.9%
Other values (7) 1230
15.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6394
81.8%
Uppercase Letter 948
 
12.1%
Space Separator 474
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1038
16.2%
c 948
14.8%
e 948
14.8%
s 948
14.8%
i 628
9.8%
b 474
7.4%
t 346
 
5.4%
a 308
 
4.8%
y 282
 
4.4%
o 192
 
3.0%
Other values (2) 282
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 474
50.0%
N 192
20.3%
P 154
 
16.2%
F 128
 
13.5%
Space Separator
ValueCountFrequency (%)
474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7342
93.9%
Common 474
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1038
14.1%
c 948
12.9%
e 948
12.9%
s 948
12.9%
i 628
8.6%
A 474
6.5%
b 474
6.5%
t 346
 
4.7%
a 308
 
4.2%
y 282
 
3.8%
Other values (6) 948
12.9%
Common
ValueCountFrequency (%)
474
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 1038
13.3%
c 948
12.1%
e 948
12.1%
s 948
12.1%
i 628
8.0%
474
 
6.1%
A 474
 
6.1%
b 474
 
6.1%
t 346
 
4.4%
a 308
 
3.9%
Other values (7) 1230
15.7%

telephone
Text

Distinct472
Distinct (%)100.0%
Missing2
Missing (%)0.4%
Memory size32.0 KiB
2023-12-09T22:46:55.283763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length12
Mean length11.99576271
Min length10

Characters and Unicode

Total characters5662
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique472 ?
Unique (%)100.0%

Sample

1st row212-228-4433
2nd row212-677-4680
3rd row212-602-9700
4th row212-677-5710
5th row212-267-5701
ValueCountFrequency (%)
2
 
0.4%
718 2
 
0.4%
929-397-3340 1
 
0.2%
212-488-3645 1
 
0.2%
718-346-0764 1
 
0.2%
718-703-5400 1
 
0.2%
212-535-8610 1
 
0.2%
718-588-8308 1
 
0.2%
212-491-4107 1
 
0.2%
718-353-0009 1
 
0.2%
Other values (465) 465
97.5%
2023-12-09T22:46:55.738909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 935
16.5%
8 708
12.5%
1 707
12.5%
7 665
11.7%
2 521
9.2%
0 452
8.0%
6 361
 
6.4%
4 358
 
6.3%
3 334
 
5.9%
5 334
 
5.9%
Other values (3) 287
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4720
83.4%
Dash Punctuation 935
 
16.5%
Space Separator 5
 
0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 708
15.0%
1 707
15.0%
7 665
14.1%
2 521
11.0%
0 452
9.6%
6 361
7.6%
4 358
7.6%
3 334
7.1%
5 334
7.1%
9 280
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 935
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5662
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 935
16.5%
8 708
12.5%
1 707
12.5%
7 665
11.7%
2 521
9.2%
0 452
8.0%
6 361
 
6.4%
4 358
 
6.3%
3 334
 
5.9%
5 334
 
5.9%
Other values (3) 287
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 935
16.5%
8 708
12.5%
1 707
12.5%
7 665
11.7%
2 521
9.2%
0 452
8.0%
6 361
 
6.4%
4 358
 
6.3%
3 334
 
5.9%
5 334
 
5.9%
Other values (3) 287
 
5.1%

independentwebsite
Text

MISSING 

Distinct275
Distinct (%)100.0%
Missing199
Missing (%)42.0%
Memory size26.6 KiB
2023-12-09T22:46:56.022663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length67
Median length41
Mean length18.48727273
Min length10

Characters and Unicode

Total characters5084
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique275 ?
Unique (%)100.0%

Sample

1st rowwww.psms34.org
2nd rowwww.ps184m.org
3rd rowwww.island188.org
4th rowwww.unmslearns.net/
5th rowwww.eschs.org
ValueCountFrequency (%)
www.bronxparkms.info 1
 
0.4%
www.is7vikings.org 1
 
0.4%
www.ps-347.org 1
 
0.4%
www.highlandparkschool.org 1
 
0.4%
www.145innovators.com 1
 
0.4%
www.ms354.com 1
 
0.4%
www.is217.org 1
 
0.4%
www.ps499formst.weebly.com 1
 
0.4%
www.scholarsnyc.com 1
 
0.4%
ms210q.schoolwires.net 1
 
0.4%
Other values (265) 265
96.4%
2023-12-09T22:46:56.686159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 819
16.1%
. 559
 
11.0%
o 440
 
8.7%
s 293
 
5.8%
r 289
 
5.7%
g 228
 
4.5%
e 214
 
4.2%
m 207
 
4.1%
c 189
 
3.7%
a 162
 
3.2%
Other values (54) 1684
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3887
76.5%
Other Punctuation 612
 
12.0%
Decimal Number 462
 
9.1%
Uppercase Letter 116
 
2.3%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 819
21.1%
o 440
11.3%
s 293
 
7.5%
r 289
 
7.4%
g 228
 
5.9%
e 214
 
5.5%
m 207
 
5.3%
c 189
 
4.9%
a 162
 
4.2%
l 141
 
3.6%
Other values (16) 905
23.3%
Uppercase Letter
ValueCountFrequency (%)
S 29
25.0%
M 11
 
9.5%
I 10
 
8.6%
A 9
 
7.8%
C 7
 
6.0%
L 5
 
4.3%
B 5
 
4.3%
E 5
 
4.3%
P 5
 
4.3%
Y 3
 
2.6%
Other values (13) 27
23.3%
Decimal Number
ValueCountFrequency (%)
1 87
18.8%
2 77
16.7%
3 58
12.6%
7 41
8.9%
4 41
8.9%
8 40
8.7%
9 33
 
7.1%
6 32
 
6.9%
0 27
 
5.8%
5 26
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 559
91.3%
/ 45
 
7.4%
: 7
 
1.1%
@ 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4003
78.7%
Common 1081
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 819
20.5%
o 440
11.0%
s 293
 
7.3%
r 289
 
7.2%
g 228
 
5.7%
e 214
 
5.3%
m 207
 
5.2%
c 189
 
4.7%
a 162
 
4.0%
l 141
 
3.5%
Other values (39) 1021
25.5%
Common
ValueCountFrequency (%)
. 559
51.7%
1 87
 
8.0%
2 77
 
7.1%
3 58
 
5.4%
/ 45
 
4.2%
7 41
 
3.8%
4 41
 
3.8%
8 40
 
3.7%
9 33
 
3.1%
6 32
 
3.0%
Other values (5) 68
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5084
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 819
16.1%
. 559
 
11.0%
o 440
 
8.7%
s 293
 
5.8%
r 289
 
5.7%
g 228
 
4.5%
e 214
 
4.2%
m 207
 
4.1%
c 189
 
3.7%
a 162
 
3.2%
Other values (54) 1684
33.1%

url
URL

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size52.3 KiB
https://www.myschools.nyc/en/schools/middle-school/9913
 
1
https://www.myschools.nyc/en/schools/middle-school/10235
 
1
https://www.myschools.nyc/en/schools/middle-school/12466
 
1
https://www.myschools.nyc/en/schools/middle-school/10095
 
1
https://www.myschools.nyc/en/schools/middle-school/11363
 
1
Other values (469)
469 
ValueCountFrequency (%)
https://www.myschools.nyc/en/schools/middle-school/9913 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/10235 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/12466 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/10095 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/11363 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/9281 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/9022 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/12609 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/9936 1
 
0.2%
https://www.myschools.nyc/en/schools/middle-school/11206 1
 
0.2%
Other values (464) 464
97.9%
ValueCountFrequency (%)
https 474
100.0%
ValueCountFrequency (%)
www.myschools.nyc 474
100.0%
ValueCountFrequency (%)
/en/schools/middle-school/10568 1
 
0.2%
/en/schools/middle-school/12631 1
 
0.2%
/en/schools/middle-school/10512 1
 
0.2%
/en/schools/middle-school/9191 1
 
0.2%
/en/schools/middle-school/12614 1
 
0.2%
/en/schools/middle-school/11264 1
 
0.2%
/en/schools/middle-school/12171 1
 
0.2%
/en/schools/middle-school/13250 1
 
0.2%
/en/schools/middle-school/10891 1
 
0.2%
/en/schools/middle-school/9726 1
 
0.2%
Other values (464) 464
97.9%
ValueCountFrequency (%)
474
100.0%
ValueCountFrequency (%)
474
100.0%

subway
Text

MISSING 

Distinct264
Distinct (%)76.1%
Missing127
Missing (%)26.8%
Memory size36.4 KiB
2023-12-09T22:46:57.114475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length187
Median length85
Mean length38.2795389
Min length7

Characters and Unicode

Total characters13283
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201 ?
Unique (%)57.9%

Sample

1st rowL to 1st Ave
2nd rowF, J, M, Z to Delancey St-Essex St
3rd rowJ, M, Z to Delancey St-Essex St; F to East Broadway
4th rowJ, M, Z to Delancey St-Essex St; F to East Broadway; B, D to Grand St
5th rowF, J, M, Z to Delancey St-Essex St; B, D to Grand St
ValueCountFrequency (%)
to 605
 
18.7%
st 270
 
8.3%
ave 206
 
6.4%
b 88
 
2.7%
2 86
 
2.7%
79
 
2.4%
5 78
 
2.4%
d 74
 
2.3%
c 71
 
2.2%
a 69
 
2.1%
Other values (356) 1610
49.8%
2023-12-09T22:46:57.717277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2889
21.7%
t 1456
 
11.0%
o 921
 
6.9%
e 605
 
4.6%
, 480
 
3.6%
a 433
 
3.3%
S 396
 
3.0%
r 391
 
2.9%
h 326
 
2.5%
n 315
 
2.4%
Other values (62) 5071
38.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6307
47.5%
Space Separator 2889
21.7%
Uppercase Letter 1970
 
14.8%
Decimal Number 1177
 
8.9%
Other Punctuation 746
 
5.6%
Dash Punctuation 186
 
1.4%
Control 8
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 396
20.1%
A 312
15.8%
B 175
 
8.9%
C 152
 
7.7%
D 98
 
5.0%
F 86
 
4.4%
R 78
 
4.0%
M 76
 
3.9%
N 70
 
3.6%
P 67
 
3.4%
Other values (17) 460
23.4%
Lowercase Letter
ValueCountFrequency (%)
t 1456
23.1%
o 921
14.6%
e 605
9.6%
a 433
 
6.9%
r 391
 
6.2%
h 326
 
5.2%
n 315
 
5.0%
s 265
 
4.2%
v 257
 
4.1%
d 198
 
3.1%
Other values (15) 1140
18.1%
Decimal Number
ValueCountFrequency (%)
1 287
24.4%
2 156
13.3%
5 141
12.0%
3 131
11.1%
4 124
10.5%
6 122
10.4%
7 75
 
6.4%
8 53
 
4.5%
9 44
 
3.7%
0 44
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 480
64.3%
; 260
34.9%
& 3
 
0.4%
/ 2
 
0.3%
. 1
 
0.1%
Control
ValueCountFrequency (%)
‚ 4
50.0%
ƒ 3
37.5%
— 1
 
12.5%
Space Separator
ValueCountFrequency (%)
2889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8277
62.3%
Common 5006
37.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1456
17.6%
o 921
 
11.1%
e 605
 
7.3%
a 433
 
5.2%
S 396
 
4.8%
r 391
 
4.7%
h 326
 
3.9%
n 315
 
3.8%
A 312
 
3.8%
s 265
 
3.2%
Other values (42) 2857
34.5%
Common
ValueCountFrequency (%)
2889
57.7%
, 480
 
9.6%
1 287
 
5.7%
; 260
 
5.2%
- 186
 
3.7%
2 156
 
3.1%
5 141
 
2.8%
3 131
 
2.6%
4 124
 
2.5%
6 122
 
2.4%
Other values (10) 230
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13267
99.9%
None 16
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2889
21.8%
t 1456
 
11.0%
o 921
 
6.9%
e 605
 
4.6%
, 480
 
3.6%
a 433
 
3.3%
S 396
 
3.0%
r 391
 
2.9%
h 326
 
2.5%
n 315
 
2.4%
Other values (57) 5055
38.1%
None
ValueCountFrequency (%)
à 4
25.0%
 4
25.0%
‚ 4
25.0%
ƒ 3
18.8%
— 1
 
6.2%

bus
Text

MISSING 

Distinct381
Distinct (%)82.1%
Missing10
Missing (%)2.1%
Memory size48.7 KiB
2023-12-09T22:46:58.210050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length255
Median length93
Mean length49.40517241
Min length2

Characters and Unicode

Total characters22924
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)66.4%

Sample

1st rowM14A, M14D, M21, M23, M8, M9, X14, X2, X42, X5
2nd rowB39, M14A, M14D, M15, M15-SBS, M21, M22, M9
3rd rowM14A, M14D, M15, M15-SBS, M21, M22, M9, X14, X37, X38
4th rowM14A, M14D, M21, M22, M8, M9
5th rowB39, M14A, M14D, M15, M15-SBS, M21, M22, M9, X14, X37, X38
ValueCountFrequency (%)
bx15 57
 
1.3%
m101 54
 
1.2%
m3 51
 
1.2%
bxm4 48
 
1.1%
bx41 48
 
1.1%
bx2 46
 
1.0%
bx41-sbs 46
 
1.0%
m5 45
 
1.0%
bx1 44
 
1.0%
bx32 42
 
1.0%
Other values (319) 3912
89.1%
2023-12-09T22:46:58.877990image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 3934
17.2%
3929
17.1%
B 2388
10.4%
1 1882
8.2%
M 1356
 
5.9%
x 1215
 
5.3%
4 1050
 
4.6%
2 993
 
4.3%
Q 893
 
3.9%
3 851
 
3.7%
Other values (13) 4433
19.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7975
34.8%
Uppercase Letter 5666
24.7%
Other Punctuation 3935
17.2%
Space Separator 3929
17.1%
Lowercase Letter 1215
 
5.3%
Dash Punctuation 204
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1882
23.6%
4 1050
13.2%
2 993
12.5%
3 851
10.7%
5 659
 
8.3%
6 654
 
8.2%
0 636
 
8.0%
7 465
 
5.8%
8 464
 
5.8%
9 321
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2388
42.1%
M 1356
23.9%
Q 893
 
15.8%
S 519
 
9.2%
X 408
 
7.2%
A 77
 
1.4%
D 19
 
0.3%
J 6
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 3934
> 99.9%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
3929
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 1215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16043
70.0%
Latin 6881
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 3934
24.5%
3929
24.5%
1 1882
11.7%
4 1050
 
6.5%
2 993
 
6.2%
3 851
 
5.3%
5 659
 
4.1%
6 654
 
4.1%
0 636
 
4.0%
7 465
 
2.9%
Other values (4) 990
 
6.2%
Latin
ValueCountFrequency (%)
B 2388
34.7%
M 1356
19.7%
x 1215
17.7%
Q 893
 
13.0%
S 519
 
7.5%
X 408
 
5.9%
A 77
 
1.1%
D 19
 
0.3%
J 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22924
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 3934
17.2%
3929
17.1%
B 2388
10.4%
1 1882
8.2%
M 1356
 
5.9%
x 1215
 
5.3%
4 1050
 
4.6%
2 993
 
4.3%
Q 893
 
3.9%
3 851
 
3.7%
Other values (13) 4433
19.3%

code_prog1
Text

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.8 KiB
2023-12-09T22:46:59.292539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.012658228
Min length5

Characters and Unicode

Total characters2376
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)100.0%

Sample

1st rowM034L
2nd rowM140S
3rd rowM184S
4th rowM188S
5th rowM332R
ValueCountFrequency (%)
k084l 1
 
0.2%
k089m 1
 
0.2%
k318m 1
 
0.2%
m670m 1
 
0.2%
q262s 1
 
0.2%
k136m 1
 
0.2%
k763l 1
 
0.2%
x279z 1
 
0.2%
m072l 1
 
0.2%
m372l 1
 
0.2%
Other values (464) 464
97.9%
2023-12-09T22:46:59.816447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 227
 
9.6%
1 193
 
8.1%
M 188
 
7.9%
0 170
 
7.2%
3 170
 
7.2%
U 151
 
6.4%
K 143
 
6.0%
4 129
 
5.4%
8 124
 
5.2%
X 116
 
4.9%
Other values (11) 765
32.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1422
59.8%
Uppercase Letter 954
40.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 188
19.7%
U 151
15.8%
K 143
15.0%
X 116
12.2%
Q 105
11.0%
L 81
8.5%
S 52
 
5.5%
A 51
 
5.3%
Z 42
 
4.4%
R 22
 
2.3%
Decimal Number
ValueCountFrequency (%)
2 227
16.0%
1 193
13.6%
0 170
12.0%
3 170
12.0%
4 129
9.1%
8 124
8.7%
6 112
7.9%
5 106
7.5%
7 96
6.8%
9 95
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1422
59.8%
Latin 954
40.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 188
19.7%
U 151
15.8%
K 143
15.0%
X 116
12.2%
Q 105
11.0%
L 81
8.5%
S 52
 
5.5%
A 51
 
5.3%
Z 42
 
4.4%
R 22
 
2.3%
Common
ValueCountFrequency (%)
2 227
16.0%
1 193
13.6%
0 170
12.0%
3 170
12.0%
4 129
9.1%
8 124
8.7%
6 112
7.9%
5 106
7.5%
7 96
6.8%
9 95
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 227
 
9.6%
1 193
 
8.1%
M 188
 
7.9%
0 170
 
7.2%
3 170
 
7.2%
U 151
 
6.4%
K 143
 
6.0%
4 129
 
5.4%
8 124
 
5.2%
X 116
 
4.9%
Other values (11) 765
32.2%

name_prog1
Text

Distinct453
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size42.2 KiB
2023-12-09T22:47:00.182789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length59
Mean length33.85654008
Min length4

Characters and Unicode

Total characters16048
Distinct characters74
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique444 ?
Unique (%)93.7%

Sample

1st rowFranklin Delano Roosevelt (P.S. 34)
2nd rowNathan Straus Preparatory School (P.S. 140)
3rd rowShuang Wen (P.S. 184) Chinese Dual Language Program
4th rowThe Island School (P.S. 188)
5th rowNext Generation Extended Learning @ NYU
ValueCountFrequency (%)
school 192
 
7.9%
the 98
 
4.0%
program 91
 
3.8%
academy 81
 
3.3%
for 61
 
2.5%
middle 52
 
2.1%
m.s 46
 
1.9%
of 46
 
1.9%
i.s 44
 
1.8%
and 42
 
1.7%
Other values (802) 1669
68.9%
2023-12-09T22:47:00.727583image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1948
 
12.1%
e 1168
 
7.3%
o 1096
 
6.8%
a 927
 
5.8%
r 786
 
4.9%
n 741
 
4.6%
l 682
 
4.2%
S 609
 
3.8%
i 580
 
3.6%
. 557
 
3.5%
Other values (64) 6954
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10021
62.4%
Uppercase Letter 2481
 
15.5%
Space Separator 1948
 
12.1%
Other Punctuation 703
 
4.4%
Decimal Number 562
 
3.5%
Open Punctuation 161
 
1.0%
Close Punctuation 161
 
1.0%
Dash Punctuation 10
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1168
11.7%
o 1096
10.9%
a 927
 
9.3%
r 786
 
7.8%
n 741
 
7.4%
l 682
 
6.8%
i 580
 
5.8%
t 525
 
5.2%
c 516
 
5.1%
h 489
 
4.9%
Other values (16) 2511
25.1%
Uppercase Letter
ValueCountFrequency (%)
S 609
24.5%
P 257
10.4%
M 239
 
9.6%
A 206
 
8.3%
I 144
 
5.8%
T 140
 
5.6%
C 121
 
4.9%
L 102
 
4.1%
E 86
 
3.5%
H 77
 
3.1%
Other values (16) 500
20.2%
Decimal Number
ValueCountFrequency (%)
2 103
18.3%
1 100
17.8%
8 59
10.5%
3 55
9.8%
9 45
8.0%
7 43
7.7%
5 42
7.5%
4 42
7.5%
6 38
 
6.8%
0 35
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 557
79.2%
/ 64
 
9.1%
& 25
 
3.6%
, 20
 
2.8%
: 19
 
2.7%
' 16
 
2.3%
@ 2
 
0.3%
Space Separator
ValueCountFrequency (%)
1948
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12502
77.9%
Common 3546
 
22.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1168
 
9.3%
o 1096
 
8.8%
a 927
 
7.4%
r 786
 
6.3%
n 741
 
5.9%
l 682
 
5.5%
S 609
 
4.9%
i 580
 
4.6%
t 525
 
4.2%
c 516
 
4.1%
Other values (42) 4872
39.0%
Common
ValueCountFrequency (%)
1948
54.9%
. 557
 
15.7%
( 161
 
4.5%
) 161
 
4.5%
2 103
 
2.9%
1 100
 
2.8%
/ 64
 
1.8%
8 59
 
1.7%
3 55
 
1.6%
9 45
 
1.3%
Other values (12) 293
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1948
 
12.1%
e 1168
 
7.3%
o 1096
 
6.8%
a 927
 
5.8%
r 786
 
4.9%
n 741
 
4.6%
l 682
 
4.2%
S 609
 
3.8%
i 580
 
3.6%
. 557
 
3.5%
Other values (64) 6954
43.3%

admissionsmethod_prog1
Text

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size29.8 KiB
2023-12-09T22:47:00.901771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length4
Mean length7.052742616
Min length4

Characters and Unicode

Total characters3343
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOpen
2nd rowScreened
3rd rowScreened: Language
4th rowScreened
5th rowScreened
ValueCountFrequency (%)
open 244
43.8%
screened 137
24.6%
composite 45
 
8.1%
score 45
 
8.1%
zoned 42
 
7.5%
language 32
 
5.7%
talent 6
 
1.1%
test 6
 
1.1%
2023-12-09T22:47:01.198865image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 831
24.9%
n 461
13.8%
p 289
 
8.6%
O 244
 
7.3%
S 182
 
5.4%
c 182
 
5.4%
r 182
 
5.4%
d 179
 
5.4%
o 177
 
5.3%
83
 
2.5%
Other values (13) 533
15.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2671
79.9%
Uppercase Letter 557
 
16.7%
Space Separator 83
 
2.5%
Other Punctuation 32
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 831
31.1%
n 461
17.3%
p 289
 
10.8%
c 182
 
6.8%
r 182
 
6.8%
d 179
 
6.7%
o 177
 
6.6%
a 70
 
2.6%
g 64
 
2.4%
t 57
 
2.1%
Other values (5) 179
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
O 244
43.8%
S 182
32.7%
C 45
 
8.1%
Z 42
 
7.5%
L 32
 
5.7%
T 12
 
2.2%
Space Separator
ValueCountFrequency (%)
83
100.0%
Other Punctuation
ValueCountFrequency (%)
: 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3228
96.6%
Common 115
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 831
25.7%
n 461
14.3%
p 289
 
9.0%
O 244
 
7.6%
S 182
 
5.6%
c 182
 
5.6%
r 182
 
5.6%
d 179
 
5.5%
o 177
 
5.5%
a 70
 
2.2%
Other values (11) 431
13.4%
Common
ValueCountFrequency (%)
83
72.2%
: 32
 
27.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3343
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 831
24.9%
n 461
13.8%
p 289
 
8.6%
O 244
 
7.3%
S 182
 
5.4%
c 182
 
5.4%
r 182
 
5.4%
d 179
 
5.4%
o 177
 
5.3%
83
 
2.5%
Other values (13) 533
15.9%

geapps_prog1
Text

Distinct340
Distinct (%)71.9%
Missing1
Missing (%)0.2%
Memory size27.8 KiB
2023-12-09T22:47:01.695448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.868921776
Min length1

Characters and Unicode

Total characters1357
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique239 ?
Unique (%)50.5%

Sample

1st row66
2nd row82
3rd row224
4th row56
5th row59
ValueCountFrequency (%)
274 5
 
1.1%
153 4
 
0.8%
218 4
 
0.8%
143 4
 
0.8%
137 4
 
0.8%
76 4
 
0.8%
159 3
 
0.6%
128 3
 
0.6%
290 3
 
0.6%
140 3
 
0.6%
Other values (330) 436
92.2%
2023-12-09T22:47:02.325817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 237
17.5%
2 187
13.8%
3 153
11.3%
4 143
10.5%
6 119
8.8%
5 119
8.8%
7 111
8.2%
8 102
7.5%
9 95
7.0%
0 91
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1357
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 237
17.5%
2 187
13.8%
3 153
11.3%
4 143
10.5%
6 119
8.8%
5 119
8.8%
7 111
8.2%
8 102
7.5%
9 95
7.0%
0 91
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1357
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 237
17.5%
2 187
13.8%
3 153
11.3%
4 143
10.5%
6 119
8.8%
5 119
8.8%
7 111
8.2%
8 102
7.5%
9 95
7.0%
0 91
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1357
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 237
17.5%
2 187
13.8%
3 153
11.3%
4 143
10.5%
6 119
8.8%
5 119
8.8%
7 111
8.2%
8 102
7.5%
9 95
7.0%
0 91
 
6.7%

swdapps_prog1
Text

Distinct153
Distinct (%)32.3%
Missing1
Missing (%)0.2%
Memory size27.5 KiB
2023-12-09T22:47:02.760894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.147991543
Min length1

Characters and Unicode

Total characters1016
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)9.7%

Sample

1st row32
2nd row56
3rd row39
4th row40
5th row25
ValueCountFrequency (%)
55 13
 
2.7%
32 10
 
2.1%
50 8
 
1.7%
34 8
 
1.7%
24 8
 
1.7%
65 8
 
1.7%
18 8
 
1.7%
73 8
 
1.7%
21 7
 
1.5%
42 7
 
1.5%
Other values (143) 388
82.0%
2023-12-09T22:47:03.330627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 172
16.9%
5 126
12.4%
2 116
11.4%
4 116
11.4%
3 108
10.6%
6 84
8.3%
7 79
7.8%
9 79
7.8%
8 73
7.2%
0 63
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1016
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 172
16.9%
5 126
12.4%
2 116
11.4%
4 116
11.4%
3 108
10.6%
6 84
8.3%
7 79
7.8%
9 79
7.8%
8 73
7.2%
0 63
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1016
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 172
16.9%
5 126
12.4%
2 116
11.4%
4 116
11.4%
3 108
10.6%
6 84
8.3%
7 79
7.8%
9 79
7.8%
8 73
7.2%
0 63
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 172
16.9%
5 126
12.4%
2 116
11.4%
4 116
11.4%
3 108
10.6%
6 84
8.3%
7 79
7.8%
9 79
7.8%
8 73
7.2%
0 63
 
6.2%

geappsperseat_prog1
Text

Distinct32
Distinct (%)6.8%
Missing4
Missing (%)0.8%
Memory size26.9 KiB
2023-12-09T22:47:03.516112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.112765957
Min length1

Characters and Unicode

Total characters523
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.1%

Sample

1st row2
2nd row2
3rd row3
4th row1
5th row3
ValueCountFrequency (%)
2 95
20.2%
3 82
17.4%
1 81
17.2%
4 43
9.1%
5 42
8.9%
7 26
 
5.5%
6 24
 
5.1%
8 12
 
2.6%
9 7
 
1.5%
10 7
 
1.5%
Other values (22) 51
10.9%
2023-12-09T22:47:03.802605image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 126
24.1%
2 109
20.8%
3 90
17.2%
4 49
 
9.4%
5 48
 
9.2%
7 31
 
5.9%
6 29
 
5.5%
8 16
 
3.1%
0 16
 
3.1%
9 9
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 523
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 126
24.1%
2 109
20.8%
3 90
17.2%
4 49
 
9.4%
5 48
 
9.2%
7 31
 
5.9%
6 29
 
5.5%
8 16
 
3.1%
0 16
 
3.1%
9 9
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 523
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 126
24.1%
2 109
20.8%
3 90
17.2%
4 49
 
9.4%
5 48
 
9.2%
7 31
 
5.9%
6 29
 
5.5%
8 16
 
3.1%
0 16
 
3.1%
9 9
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 523
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 126
24.1%
2 109
20.8%
3 90
17.2%
4 49
 
9.4%
5 48
 
9.2%
7 31
 
5.9%
6 29
 
5.5%
8 16
 
3.1%
0 16
 
3.1%
9 9
 
1.7%

swdappsperseat_prog1
Text

MISSING 

Distinct24
Distinct (%)5.3%
Missing19
Missing (%)4.0%
Memory size26.5 KiB
2023-12-09T22:47:03.977612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.092307692
Min length1

Characters and Unicode

Total characters497
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.1%

Sample

1st row2
2nd row3
3rd row2
4th row3
5th row8
ValueCountFrequency (%)
2 84
18.5%
3 79
17.4%
4 71
15.6%
1 51
11.2%
5 45
9.9%
6 30
 
6.6%
7 18
 
4.0%
9 14
 
3.1%
8 12
 
2.6%
0 9
 
2.0%
Other values (14) 42
9.2%
2023-12-09T22:47:04.262575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 95
19.1%
1 93
18.7%
3 85
17.1%
4 72
14.5%
5 48
9.7%
6 34
 
6.8%
7 19
 
3.8%
8 19
 
3.8%
9 18
 
3.6%
0 14
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 497
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 95
19.1%
1 93
18.7%
3 85
17.1%
4 72
14.5%
5 48
9.7%
6 34
 
6.8%
7 19
 
3.8%
8 19
 
3.8%
9 18
 
3.6%
0 14
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 497
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 95
19.1%
1 93
18.7%
3 85
17.1%
4 72
14.5%
5 48
9.7%
6 34
 
6.8%
7 19
 
3.8%
8 19
 
3.8%
9 18
 
3.6%
0 14
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 497
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 95
19.1%
1 93
18.7%
3 85
17.1%
4 72
14.5%
5 48
9.7%
6 34
 
6.8%
7 19
 
3.8%
8 19
 
3.8%
9 18
 
3.6%
0 14
 
2.8%

swdseats_prog1
Text

Distinct62
Distinct (%)13.1%
Missing2
Missing (%)0.4%
Memory size27.3 KiB
2023-12-09T22:47:04.526916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.786016949
Min length1

Characters and Unicode

Total characters843
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)4.4%

Sample

1st row16
2nd row17
3rd row17
4th row12
5th row3
ValueCountFrequency (%)
12 34
 
7.2%
17 32
 
6.8%
5 28
 
5.9%
13 22
 
4.7%
11 21
 
4.4%
15 19
 
4.0%
6 18
 
3.8%
16 17
 
3.6%
23 17
 
3.6%
0 17
 
3.6%
Other values (52) 247
52.3%
2023-12-09T22:47:04.949992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 247
29.3%
2 168
19.9%
3 74
 
8.8%
5 73
 
8.7%
6 63
 
7.5%
0 54
 
6.4%
7 48
 
5.7%
4 47
 
5.6%
8 38
 
4.5%
9 31
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 843
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 247
29.3%
2 168
19.9%
3 74
 
8.8%
5 73
 
8.7%
6 63
 
7.5%
0 54
 
6.4%
7 48
 
5.7%
4 47
 
5.6%
8 38
 
4.5%
9 31
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 843
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 247
29.3%
2 168
19.9%
3 74
 
8.8%
5 73
 
8.7%
6 63
 
7.5%
0 54
 
6.4%
7 48
 
5.7%
4 47
 
5.6%
8 38
 
4.5%
9 31
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 843
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 247
29.3%
2 168
19.9%
3 74
 
8.8%
5 73
 
8.7%
6 63
 
7.5%
0 54
 
6.4%
7 48
 
5.7%
4 47
 
5.6%
8 38
 
4.5%
9 31
 
3.7%

geseats_prog1
Text

Distinct140
Distinct (%)29.7%
Missing2
Missing (%)0.4%
Memory size27.5 KiB
2023-12-09T22:47:05.356535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.201271186
Min length1

Characters and Unicode

Total characters1039
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)13.3%

Sample

1st row44
2nd row48
3rd row71
4th row44
5th row22
ValueCountFrequency (%)
25 20
 
4.2%
49 20
 
4.2%
48 20
 
4.2%
73 19
 
4.0%
24 15
 
3.2%
74 14
 
3.0%
71 13
 
2.8%
72 11
 
2.3%
75 11
 
2.3%
47 8
 
1.7%
Other values (130) 321
68.0%
2023-12-09T22:47:05.902585image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 145
14.0%
1 138
13.3%
4 130
12.5%
5 121
11.6%
2 116
11.2%
9 81
7.8%
8 78
7.5%
3 78
7.5%
6 78
7.5%
0 74
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1039
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 145
14.0%
1 138
13.3%
4 130
12.5%
5 121
11.6%
2 116
11.2%
9 81
7.8%
8 78
7.5%
3 78
7.5%
6 78
7.5%
0 74
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1039
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 145
14.0%
1 138
13.3%
4 130
12.5%
5 121
11.6%
2 116
11.2%
9 81
7.8%
8 78
7.5%
3 78
7.5%
6 78
7.5%
0 74
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1039
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 145
14.0%
1 138
13.3%
4 130
12.5%
5 121
11.6%
2 116
11.2%
9 81
7.8%
8 78
7.5%
3 78
7.5%
6 78
7.5%
0 74
7.1%

gefilled_prog1
Text

Distinct2
Distinct (%)0.4%
Missing2
Missing (%)0.4%
Memory size26.9 KiB
2023-12-09T22:47:06.023996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters472
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowY
4th rowN
5th rowN
ValueCountFrequency (%)
n 241
51.1%
y 231
48.9%
2023-12-09T22:47:06.234964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 241
51.1%
Y 231
48.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 472
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 241
51.1%
Y 231
48.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 472
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 241
51.1%
Y 231
48.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 241
51.1%
Y 231
48.9%

swdfilled_prog1
Text

Distinct2
Distinct (%)0.4%
Missing2
Missing (%)0.4%
Memory size26.9 KiB
2023-12-09T22:47:06.340275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters472
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowN
4th rowY
5th rowY
ValueCountFrequency (%)
y 271
57.4%
n 201
42.6%
2023-12-09T22:47:06.549461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 271
57.4%
N 201
42.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 472
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 271
57.4%
N 201
42.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 472
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 271
57.4%
N 201
42.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 271
57.4%
N 201
42.6%

eligibility_prog1
Text

Distinct66
Distinct (%)14.0%
Missing1
Missing (%)0.2%
Memory size47.9 KiB
2023-12-09T22:47:06.799998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length105
Median length95
Mean length46.3192389
Min length31

Characters and Unicode

Total characters21909
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)5.1%

Sample

1st rowOpen to students and residents of District 1
2nd rowOpen to students and residents of District 1
3rd rowOpen to students and residents of Manhattan
4th rowOpen to students and residents of District 1
5th rowOpen to students and residents of District 1
ValueCountFrequency (%)
students 486
12.4%
open 473
12.1%
to 473
12.1%
and 452
11.6%
residents 431
11.0%
of 418
10.7%
district 231
 
5.9%
the 155
 
4.0%
bronx 116
 
3.0%
in 40
 
1.0%
Other values (55) 631
16.2%
2023-12-09T22:47:07.503951image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3433
15.7%
t 2634
12.0%
n 2261
10.3%
e 2192
10.0%
s 2184
10.0%
d 1447
 
6.6%
o 1215
 
5.5%
i 1117
 
5.1%
r 926
 
4.2%
a 549
 
2.5%
Other values (40) 3951
18.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17001
77.6%
Space Separator 3433
 
15.7%
Uppercase Letter 950
 
4.3%
Decimal Number 477
 
2.2%
Other Punctuation 38
 
0.2%
Dash Punctuation 10
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2634
15.5%
n 2261
13.3%
e 2192
12.9%
s 2184
12.8%
d 1447
8.5%
o 1215
7.1%
i 1117
6.6%
r 926
 
5.4%
a 549
 
3.2%
u 541
 
3.2%
Other values (13) 1935
11.4%
Uppercase Letter
ValueCountFrequency (%)
O 464
48.8%
D 240
25.3%
B 141
 
14.8%
Q 24
 
2.5%
C 17
 
1.8%
Y 17
 
1.8%
N 17
 
1.8%
M 13
 
1.4%
A 10
 
1.1%
S 5
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 124
26.0%
1 92
19.3%
5 62
13.0%
3 54
11.3%
6 33
 
6.9%
9 32
 
6.7%
0 23
 
4.8%
4 20
 
4.2%
8 20
 
4.2%
7 17
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 14
36.8%
; 11
28.9%
, 9
23.7%
& 4
 
10.5%
Space Separator
ValueCountFrequency (%)
3433
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17951
81.9%
Common 3958
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2634
14.7%
n 2261
12.6%
e 2192
12.2%
s 2184
12.2%
d 1447
8.1%
o 1215
6.8%
i 1117
 
6.2%
r 926
 
5.2%
a 549
 
3.1%
u 541
 
3.0%
Other values (24) 2885
16.1%
Common
ValueCountFrequency (%)
3433
86.7%
2 124
 
3.1%
1 92
 
2.3%
5 62
 
1.6%
3 54
 
1.4%
6 33
 
0.8%
9 32
 
0.8%
0 23
 
0.6%
4 20
 
0.5%
8 20
 
0.5%
Other values (6) 65
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21909
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3433
15.7%
t 2634
12.0%
n 2261
10.3%
e 2192
10.0%
s 2184
10.0%
d 1447
 
6.6%
o 1215
 
5.5%
i 1117
 
5.1%
r 926
 
4.2%
a 549
 
2.5%
Other values (40) 3951
18.0%

priority1_prog1
Text

MISSING 

Distinct43
Distinct (%)15.1%
Missing190
Missing (%)40.1%
Memory size33.6 KiB
2023-12-09T22:47:07.753719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length121
Median length107
Mean length42.27112676
Min length31

Characters and Unicode

Total characters12005
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)9.9%

Sample

1st rowPriority to continuing students
2nd rowPriority to continuing students
3rd rowPriority to continuing students
4th rowPriority to continuing students
5th rowPriority to continuing students
ValueCountFrequency (%)
to 293
15.8%
priority 284
15.3%
students 218
11.8%
residents 158
8.5%
continuing 116
 
6.3%
and 96
 
5.2%
district 84
 
4.5%
of 79
 
4.3%
the 78
 
4.2%
school 74
 
4.0%
Other values (77) 373
20.1%
2023-12-09T22:47:08.139568image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1589
13.2%
1569
13.1%
i 1222
10.2%
o 1019
8.5%
n 940
7.8%
s 910
7.6%
r 841
 
7.0%
e 805
 
6.7%
d 645
 
5.4%
u 337
 
2.8%
Other values (35) 2128
17.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9701
80.8%
Space Separator 1569
 
13.1%
Uppercase Letter 471
 
3.9%
Decimal Number 238
 
2.0%
Other Punctuation 26
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1589
16.4%
i 1222
12.6%
o 1019
10.5%
n 940
9.7%
s 910
9.4%
r 841
8.7%
e 805
8.3%
d 645
6.6%
u 337
 
3.5%
y 289
 
3.0%
Other values (9) 1104
11.4%
Uppercase Letter
ValueCountFrequency (%)
P 323
68.6%
D 86
 
18.3%
S 43
 
9.1%
G 4
 
0.8%
T 4
 
0.8%
R 3
 
0.6%
I 2
 
0.4%
C 2
 
0.4%
A 2
 
0.4%
L 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 78
32.8%
2 32
13.4%
9 22
 
9.2%
3 21
 
8.8%
5 18
 
7.6%
0 17
 
7.1%
7 17
 
7.1%
8 16
 
6.7%
6 9
 
3.8%
4 8
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 19
73.1%
& 4
 
15.4%
. 2
 
7.7%
/ 1
 
3.8%
Space Separator
ValueCountFrequency (%)
1569
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10172
84.7%
Common 1833
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1589
15.6%
i 1222
12.0%
o 1019
10.0%
n 940
9.2%
s 910
8.9%
r 841
8.3%
e 805
7.9%
d 645
6.3%
u 337
 
3.3%
P 323
 
3.2%
Other values (20) 1541
15.1%
Common
ValueCountFrequency (%)
1569
85.6%
1 78
 
4.3%
2 32
 
1.7%
9 22
 
1.2%
3 21
 
1.1%
, 19
 
1.0%
5 18
 
1.0%
0 17
 
0.9%
7 17
 
0.9%
8 16
 
0.9%
Other values (5) 24
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1589
13.2%
1569
13.1%
i 1222
10.2%
o 1019
8.5%
n 940
7.8%
s 910
7.6%
r 841
 
7.0%
e 805
 
6.7%
d 645
 
5.4%
u 337
 
2.8%
Other values (35) 2128
17.7%

priority2_prog1
Text

MISSING 

Distinct50
Distinct (%)17.7%
Missing191
Missing (%)40.3%
Memory size33.3 KiB
2023-12-09T22:47:08.380310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length62
Mean length41.44522968
Min length31

Characters and Unicode

Total characters11729
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)8.1%

Sample

1st rowThen to District 1 students and residents
2nd rowThen to District 1 students and residents
3rd rowThen to District 1 students and residents
4th rowThen to District 1 students and residents
5th rowThen to New York City residents
ValueCountFrequency (%)
to 287
14.3%
then 281
14.0%
residents 278
13.8%
students 198
9.8%
and 198
9.8%
district 112
 
5.6%
of 82
 
4.1%
the 74
 
3.7%
school 74
 
3.7%
zone 73
 
3.6%
Other values (61) 356
17.7%
2023-12-09T22:47:08.752561image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1730
14.7%
e 1380
11.8%
t 1342
11.4%
n 1177
10.0%
s 1148
9.8%
d 741
 
6.3%
o 703
 
6.0%
i 550
 
4.7%
r 533
 
4.5%
h 435
 
3.7%
Other values (35) 1990
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9231
78.7%
Space Separator 1730
 
14.7%
Uppercase Letter 539
 
4.6%
Decimal Number 224
 
1.9%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1380
14.9%
t 1342
14.5%
n 1177
12.8%
s 1148
12.4%
d 741
8.0%
o 703
7.6%
i 550
 
6.0%
r 533
 
5.8%
h 435
 
4.7%
a 263
 
2.8%
Other values (11) 959
10.4%
Uppercase Letter
ValueCountFrequency (%)
T 281
52.1%
D 112
 
20.8%
B 74
 
13.7%
S 14
 
2.6%
P 13
 
2.4%
C 11
 
2.0%
N 10
 
1.9%
Y 10
 
1.9%
Q 5
 
0.9%
M 4
 
0.7%
Other values (2) 5
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 56
25.0%
2 46
20.5%
9 30
13.4%
8 20
 
8.9%
3 18
 
8.0%
0 16
 
7.1%
6 14
 
6.2%
5 11
 
4.9%
7 9
 
4.0%
4 4
 
1.8%
Space Separator
ValueCountFrequency (%)
1730
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9770
83.3%
Common 1959
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1380
14.1%
t 1342
13.7%
n 1177
12.0%
s 1148
11.8%
d 741
7.6%
o 703
7.2%
i 550
 
5.6%
r 533
 
5.5%
h 435
 
4.5%
T 281
 
2.9%
Other values (23) 1480
15.1%
Common
ValueCountFrequency (%)
1730
88.3%
1 56
 
2.9%
2 46
 
2.3%
9 30
 
1.5%
8 20
 
1.0%
3 18
 
0.9%
0 16
 
0.8%
6 14
 
0.7%
5 11
 
0.6%
7 9
 
0.5%
Other values (2) 9
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11729
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1730
14.7%
e 1380
11.8%
t 1342
11.4%
n 1177
10.0%
s 1148
9.8%
d 741
 
6.3%
o 703
 
6.0%
i 550
 
4.7%
r 533
 
4.5%
h 435
 
3.7%
Other values (35) 1990
17.0%

priority3_prog1
Text

MISSING 

Distinct21
Distinct (%)20.4%
Missing371
Missing (%)78.3%
Memory size21.4 KiB
2023-12-09T22:47:08.971199image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length49
Median length42
Mean length39.10679612
Min length36

Characters and Unicode

Total characters4028
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.9%

Sample

1st rowThen to Manhattan students and residents
2nd rowThen to District 2 students and residents
3rd rowThen to District 2 students and residents
4th rowThen to District 25 students and residents
5th rowThen to District 2 students and residents
ValueCountFrequency (%)
and 105
15.6%
then 103
15.3%
students 103
15.3%
residents 103
15.3%
to 103
15.3%
district 52
7.7%
bronx 44
6.5%
4 7
 
1.0%
25 7
 
1.0%
11 5
 
0.7%
Other values (17) 42
 
6.2%
2023-12-09T22:47:09.313368image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
571
14.2%
t 520
12.9%
n 467
11.6%
s 467
11.6%
e 418
10.4%
d 311
7.7%
i 207
 
5.1%
r 201
 
5.0%
o 151
 
3.7%
a 111
 
2.8%
Other values (22) 604
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3166
78.6%
Space Separator 571
 
14.2%
Uppercase Letter 206
 
5.1%
Decimal Number 85
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 520
16.4%
n 467
14.8%
s 467
14.8%
e 418
13.2%
d 311
9.8%
i 207
 
6.5%
r 201
 
6.3%
o 151
 
4.8%
a 111
 
3.5%
u 106
 
3.3%
Other values (6) 207
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 23
27.1%
2 18
21.2%
5 10
11.8%
4 8
 
9.4%
3 6
 
7.1%
9 5
 
5.9%
7 4
 
4.7%
0 4
 
4.7%
6 4
 
4.7%
8 3
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
T 103
50.0%
D 52
25.2%
B 46
22.3%
Q 3
 
1.5%
M 2
 
1.0%
Space Separator
ValueCountFrequency (%)
571
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3372
83.7%
Common 656
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 520
15.4%
n 467
13.8%
s 467
13.8%
e 418
12.4%
d 311
9.2%
i 207
 
6.1%
r 201
 
6.0%
o 151
 
4.5%
a 111
 
3.3%
u 106
 
3.1%
Other values (11) 413
12.2%
Common
ValueCountFrequency (%)
571
87.0%
1 23
 
3.5%
2 18
 
2.7%
5 10
 
1.5%
4 8
 
1.2%
3 6
 
0.9%
9 5
 
0.8%
7 4
 
0.6%
0 4
 
0.6%
6 4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4028
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
571
14.2%
t 520
12.9%
n 467
11.6%
s 467
11.6%
e 418
10.4%
d 311
7.7%
i 207
 
5.1%
r 201
 
5.0%
o 151
 
3.7%
a 111
 
2.8%
Other values (22) 604
15.0%

priority4_prog1
Text

MISSING 

Distinct3
Distinct (%)21.4%
Missing460
Missing (%)97.0%
Memory size15.8 KiB
2023-12-09T22:47:09.499019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length36
Mean length37
Min length36

Characters and Unicode

Total characters518
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)7.1%

Sample

1st rowThen to Manhattan students and residents
2nd rowThen to Manhattan students and residents
3rd rowThen to Bronx students and residents
4th rowThen to Bronx students and residents
5th rowThen to Bronx students and residents
ValueCountFrequency (%)
then 14
16.5%
to 14
16.5%
students 14
16.5%
and 14
16.5%
residents 14
16.5%
bronx 11
12.9%
manhattan 2
 
2.4%
district 1
 
1.2%
10 1
 
1.2%
2023-12-09T22:47:09.801968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 71
13.7%
71
13.7%
t 62
12.0%
s 57
11.0%
e 56
10.8%
d 42
8.1%
r 26
 
5.0%
o 25
 
4.8%
a 20
 
3.9%
i 16
 
3.1%
Other values (10) 72
13.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 417
80.5%
Space Separator 71
 
13.7%
Uppercase Letter 28
 
5.4%
Decimal Number 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 71
17.0%
t 62
14.9%
s 57
13.7%
e 56
13.4%
d 42
10.1%
r 26
 
6.2%
o 25
 
6.0%
a 20
 
4.8%
i 16
 
3.8%
h 16
 
3.8%
Other values (3) 26
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
T 14
50.0%
B 11
39.3%
M 2
 
7.1%
D 1
 
3.6%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
0 1
50.0%
Space Separator
ValueCountFrequency (%)
71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 445
85.9%
Common 73
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 71
16.0%
t 62
13.9%
s 57
12.8%
e 56
12.6%
d 42
9.4%
r 26
 
5.8%
o 25
 
5.6%
a 20
 
4.5%
i 16
 
3.6%
h 16
 
3.6%
Other values (7) 54
12.1%
Common
ValueCountFrequency (%)
71
97.3%
1 1
 
1.4%
0 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 518
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 71
13.7%
71
13.7%
t 62
12.0%
s 57
11.0%
e 56
10.8%
d 42
8.1%
r 26
 
5.0%
o 25
 
4.8%
a 20
 
3.9%
i 16
 
3.1%
Other values (10) 72
13.9%

priority5_prog1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog2
Text

MISSING 

Distinct118
Distinct (%)100.0%
Missing356
Missing (%)75.1%
Memory size18.4 KiB
2023-12-09T22:47:10.195249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.050847458
Min length5

Characters and Unicode

Total characters596
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)100.0%

Sample

1st rowM332S
2nd rowM378M
3rd rowM104N
4th rowM131N
5th rowM167N
ValueCountFrequency (%)
k229z 1
 
0.8%
k201z 1
 
0.8%
x390m 1
 
0.8%
m177s 1
 
0.8%
x127l 1
 
0.8%
m104n 1
 
0.8%
k907u 1
 
0.8%
x391z 1
 
0.8%
k259z 1
 
0.8%
k002u 1
 
0.8%
Other values (108) 108
91.5%
2023-12-09T22:47:10.711353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 57
 
9.6%
1 55
 
9.2%
0 55
 
9.2%
K 52
 
8.7%
Z 38
 
6.4%
U 36
 
6.0%
3 34
 
5.7%
8 31
 
5.2%
M 30
 
5.0%
4 29
 
4.9%
Other values (15) 179
30.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 354
59.4%
Uppercase Letter 242
40.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 52
21.5%
Z 38
15.7%
U 36
14.9%
M 30
12.4%
X 23
9.5%
Q 22
9.1%
S 10
 
4.1%
N 9
 
3.7%
R 7
 
2.9%
L 3
 
1.2%
Other values (5) 12
 
5.0%
Decimal Number
ValueCountFrequency (%)
2 57
16.1%
1 55
15.5%
0 55
15.5%
3 34
9.6%
8 31
8.8%
4 29
8.2%
7 28
7.9%
9 27
7.6%
6 22
 
6.2%
5 16
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 354
59.4%
Latin 242
40.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 52
21.5%
Z 38
15.7%
U 36
14.9%
M 30
12.4%
X 23
9.5%
Q 22
9.1%
S 10
 
4.1%
N 9
 
3.7%
R 7
 
2.9%
L 3
 
1.2%
Other values (5) 12
 
5.0%
Common
ValueCountFrequency (%)
2 57
16.1%
1 55
15.5%
0 55
15.5%
3 34
9.6%
8 31
8.8%
4 29
8.2%
7 28
7.9%
9 27
7.6%
6 22
 
6.2%
5 16
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 57
 
9.6%
1 55
 
9.2%
0 55
 
9.2%
K 52
 
8.7%
Z 38
 
6.4%
U 36
 
6.0%
3 34
 
5.7%
8 31
 
5.2%
M 30
 
5.0%
4 29
 
4.9%
Other values (15) 179
30.0%

name_prog2
Text

MISSING 

Distinct96
Distinct (%)81.4%
Missing356
Missing (%)75.1%
Memory size21.5 KiB
2023-12-09T22:47:11.128401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length53
Mean length31.79661017
Min length8

Characters and Unicode

Total characters3752
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)77.1%

Sample

1st rowUniversity Neighborhood Middle School
2nd rowSchool for Global Leaders Mandarin Dual Language Program
3rd rowSpecial Progress
4th rowSpecial Progress
5th rowSpecial Progress
ValueCountFrequency (%)
program 58
 
10.1%
zoned 31
 
5.4%
school 24
 
4.2%
i.s 22
 
3.8%
the 18
 
3.1%
m.s 13
 
2.3%
academy 13
 
2.3%
12
 
2.1%
dual 11
 
1.9%
language 11
 
1.9%
Other values (250) 362
63.0%
2023-12-09T22:47:11.734274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
457
 
12.2%
e 265
 
7.1%
r 251
 
6.7%
a 250
 
6.7%
o 245
 
6.5%
n 164
 
4.4%
. 133
 
3.5%
t 122
 
3.3%
S 121
 
3.2%
i 119
 
3.2%
Other values (57) 1625
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2308
61.5%
Uppercase Letter 580
 
15.5%
Space Separator 457
 
12.2%
Other Punctuation 166
 
4.4%
Decimal Number 158
 
4.2%
Open Punctuation 41
 
1.1%
Close Punctuation 41
 
1.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 265
11.5%
r 251
10.9%
a 250
10.8%
o 245
10.6%
n 164
 
7.1%
t 122
 
5.3%
i 119
 
5.2%
g 116
 
5.0%
l 107
 
4.6%
d 106
 
4.6%
Other values (14) 563
24.4%
Uppercase Letter
ValueCountFrequency (%)
S 121
20.9%
P 84
14.5%
M 59
10.2%
A 40
 
6.9%
I 33
 
5.7%
Z 32
 
5.5%
L 31
 
5.3%
T 28
 
4.8%
H 24
 
4.1%
C 20
 
3.4%
Other values (14) 108
18.6%
Decimal Number
ValueCountFrequency (%)
2 32
20.3%
1 22
13.9%
9 18
11.4%
8 17
10.8%
3 15
9.5%
4 12
 
7.6%
7 12
 
7.6%
0 11
 
7.0%
5 10
 
6.3%
6 9
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 133
80.1%
& 11
 
6.6%
: 10
 
6.0%
/ 8
 
4.8%
, 4
 
2.4%
Space Separator
ValueCountFrequency (%)
457
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2888
77.0%
Common 864
 
23.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 265
 
9.2%
r 251
 
8.7%
a 250
 
8.7%
o 245
 
8.5%
n 164
 
5.7%
t 122
 
4.2%
S 121
 
4.2%
i 119
 
4.1%
g 116
 
4.0%
l 107
 
3.7%
Other values (38) 1128
39.1%
Common
ValueCountFrequency (%)
457
52.9%
. 133
 
15.4%
( 41
 
4.7%
) 41
 
4.7%
2 32
 
3.7%
1 22
 
2.5%
9 18
 
2.1%
8 17
 
2.0%
3 15
 
1.7%
4 12
 
1.4%
Other values (9) 76
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
457
 
12.2%
e 265
 
7.1%
r 251
 
6.7%
a 250
 
6.7%
o 245
 
6.5%
n 164
 
4.4%
. 133
 
3.5%
t 122
 
3.3%
S 121
 
3.2%
i 119
 
3.2%
Other values (57) 1625
43.3%

admissionsmethod_prog2
Text

MISSING 

Distinct6
Distinct (%)5.1%
Missing356
Missing (%)75.1%
Memory size18.6 KiB
2023-12-09T22:47:11.915273image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length15
Mean length6.601694915
Min length4

Characters and Unicode

Total characters779
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st rowScreened
2nd rowScreened: Language
3rd rowScreened
4th rowScreened
5th rowScreened
ValueCountFrequency (%)
open 44
32.6%
zoned 38
28.1%
screened 29
21.5%
language 10
 
7.4%
talent 6
 
4.4%
test 6
 
4.4%
composite 1
 
0.7%
score 1
 
0.7%
2023-12-09T22:47:12.210004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 193
24.8%
n 127
16.3%
d 67
 
8.6%
p 45
 
5.8%
O 44
 
5.6%
o 41
 
5.3%
Z 38
 
4.9%
S 30
 
3.9%
c 30
 
3.9%
r 30
 
3.9%
Other values (13) 134
17.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 617
79.2%
Uppercase Letter 135
 
17.3%
Space Separator 17
 
2.2%
Other Punctuation 10
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 193
31.3%
n 127
20.6%
d 67
 
10.9%
p 45
 
7.3%
o 41
 
6.6%
c 30
 
4.9%
r 30
 
4.9%
a 26
 
4.2%
g 20
 
3.2%
t 13
 
2.1%
Other values (5) 25
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
O 44
32.6%
Z 38
28.1%
S 30
22.2%
T 12
 
8.9%
L 10
 
7.4%
C 1
 
0.7%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
: 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 752
96.5%
Common 27
 
3.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 193
25.7%
n 127
16.9%
d 67
 
8.9%
p 45
 
6.0%
O 44
 
5.9%
o 41
 
5.5%
Z 38
 
5.1%
S 30
 
4.0%
c 30
 
4.0%
r 30
 
4.0%
Other values (11) 107
14.2%
Common
ValueCountFrequency (%)
17
63.0%
: 10
37.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 779
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 193
24.8%
n 127
16.3%
d 67
 
8.6%
p 45
 
5.8%
O 44
 
5.6%
o 41
 
5.3%
Z 38
 
4.9%
S 30
 
3.9%
c 30
 
3.9%
r 30
 
3.9%
Other values (13) 134
17.2%

geapps_prog2
Text

MISSING 

Distinct102
Distinct (%)87.2%
Missing357
Missing (%)75.3%
Memory size18.1 KiB
2023-12-09T22:47:12.566133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.786324786
Min length1

Characters and Unicode

Total characters326
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)74.4%

Sample

1st row127
2nd row44
3rd row863
4th row158
5th row882
ValueCountFrequency (%)
423 2
 
1.7%
331 2
 
1.7%
323 2
 
1.7%
44 2
 
1.7%
347 2
 
1.7%
134 2
 
1.7%
214 2
 
1.7%
191 2
 
1.7%
157 2
 
1.7%
272 2
 
1.7%
Other values (92) 97
82.9%
2023-12-09T22:47:13.052248image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 67
20.6%
2 42
12.9%
3 42
12.9%
4 33
10.1%
6 33
10.1%
5 27
8.3%
7 27
8.3%
8 20
 
6.1%
9 19
 
5.8%
0 16
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 326
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 67
20.6%
2 42
12.9%
3 42
12.9%
4 33
10.1%
6 33
10.1%
5 27
8.3%
7 27
8.3%
8 20
 
6.1%
9 19
 
5.8%
0 16
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 326
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 67
20.6%
2 42
12.9%
3 42
12.9%
4 33
10.1%
6 33
10.1%
5 27
8.3%
7 27
8.3%
8 20
 
6.1%
9 19
 
5.8%
0 16
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 326
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 67
20.6%
2 42
12.9%
3 42
12.9%
4 33
10.1%
6 33
10.1%
5 27
8.3%
7 27
8.3%
8 20
 
6.1%
9 19
 
5.8%
0 16
 
4.9%

swdapps_prog2
Text

MISSING 

Distinct71
Distinct (%)60.7%
Missing357
Missing (%)75.3%
Memory size18.0 KiB
2023-12-09T22:47:13.344900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.025641026
Min length1

Characters and Unicode

Total characters237
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)34.2%

Sample

1st row82
2nd row7
3rd row79
4th row17
5th row85
ValueCountFrequency (%)
5 5
 
4.3%
48 4
 
3.4%
22 4
 
3.4%
13 3
 
2.6%
31 3
 
2.6%
42 3
 
2.6%
35 3
 
2.6%
106 3
 
2.6%
126 3
 
2.6%
17 3
 
2.6%
Other values (61) 83
70.9%
2023-12-09T22:47:13.763119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 37
15.6%
2 35
14.8%
5 29
12.2%
3 29
12.2%
6 28
11.8%
4 23
9.7%
8 15
6.3%
7 15
6.3%
9 15
6.3%
0 11
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 237
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
15.6%
2 35
14.8%
5 29
12.2%
3 29
12.2%
6 28
11.8%
4 23
9.7%
8 15
6.3%
7 15
6.3%
9 15
6.3%
0 11
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 237
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 37
15.6%
2 35
14.8%
5 29
12.2%
3 29
12.2%
6 28
11.8%
4 23
9.7%
8 15
6.3%
7 15
6.3%
9 15
6.3%
0 11
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 37
15.6%
2 35
14.8%
5 29
12.2%
3 29
12.2%
6 28
11.8%
4 23
9.7%
8 15
6.3%
7 15
6.3%
9 15
6.3%
0 11
 
4.6%

geappsperseat_prog2
Text

MISSING 

Distinct18
Distinct (%)15.5%
Missing358
Missing (%)75.5%
Memory size17.9 KiB
2023-12-09T22:47:13.907140image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.086206897
Min length1

Characters and Unicode

Total characters126
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)6.9%

Sample

1st row2
2nd row2
3rd row4
4th row4
5th row4
ValueCountFrequency (%)
1 41
35.3%
2 23
19.8%
4 12
 
10.3%
3 11
 
9.5%
7 6
 
5.2%
5 6
 
5.2%
8 3
 
2.6%
10 2
 
1.7%
6 2
 
1.7%
0 2
 
1.7%
Other values (8) 8
 
6.9%
2023-12-09T22:47:14.155447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 47
37.3%
2 29
23.0%
4 13
 
10.3%
3 13
 
10.3%
5 7
 
5.6%
7 6
 
4.8%
8 4
 
3.2%
0 4
 
3.2%
6 3
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 47
37.3%
2 29
23.0%
4 13
 
10.3%
3 13
 
10.3%
5 7
 
5.6%
7 6
 
4.8%
8 4
 
3.2%
0 4
 
3.2%
6 3
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 126
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 47
37.3%
2 29
23.0%
4 13
 
10.3%
3 13
 
10.3%
5 7
 
5.6%
7 6
 
4.8%
8 4
 
3.2%
0 4
 
3.2%
6 3
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 47
37.3%
2 29
23.0%
4 13
 
10.3%
3 13
 
10.3%
5 7
 
5.6%
7 6
 
4.8%
8 4
 
3.2%
0 4
 
3.2%
6 3
 
2.4%

swdappsperseat_prog2
Text

MISSING 

Distinct16
Distinct (%)14.3%
Missing362
Missing (%)76.4%
Memory size17.8 KiB
2023-12-09T22:47:14.287942image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.080357143
Min length1

Characters and Unicode

Total characters121
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.4%

Sample

1st row3
2nd row1
3rd row2
4th row2
5th row1
ValueCountFrequency (%)
1 35
31.2%
2 20
17.9%
3 14
 
12.5%
4 12
 
10.7%
6 7
 
6.2%
0 6
 
5.4%
5 4
 
3.6%
11 3
 
2.7%
8 3
 
2.7%
10 2
 
1.8%
Other values (6) 6
 
5.4%
2023-12-09T22:47:14.531706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 46
38.0%
2 21
17.4%
3 15
 
12.4%
4 12
 
9.9%
0 8
 
6.6%
6 7
 
5.8%
5 6
 
5.0%
8 4
 
3.3%
7 1
 
0.8%
9 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 121
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 46
38.0%
2 21
17.4%
3 15
 
12.4%
4 12
 
9.9%
0 8
 
6.6%
6 7
 
5.8%
5 6
 
5.0%
8 4
 
3.3%
7 1
 
0.8%
9 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 121
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 46
38.0%
2 21
17.4%
3 15
 
12.4%
4 12
 
9.9%
0 8
 
6.6%
6 7
 
5.8%
5 6
 
5.0%
8 4
 
3.3%
7 1
 
0.8%
9 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 46
38.0%
2 21
17.4%
3 15
 
12.4%
4 12
 
9.9%
0 8
 
6.6%
6 7
 
5.8%
5 6
 
5.0%
8 4
 
3.3%
7 1
 
0.8%
9 1
 
0.8%

swdseats_prog2
Text

MISSING 

Distinct52
Distinct (%)44.4%
Missing357
Missing (%)75.3%
Memory size18.0 KiB
2023-12-09T22:47:14.767720image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.717948718
Min length1

Characters and Unicode

Total characters201
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)23.1%

Sample

1st row24
2nd row6
3rd row47
4th row10
5th row60
ValueCountFrequency (%)
5 9
 
7.7%
6 9
 
7.7%
11 7
 
6.0%
12 7
 
6.0%
0 5
 
4.3%
9 5
 
4.3%
17 4
 
3.4%
16 4
 
3.4%
15 4
 
3.4%
18 3
 
2.6%
Other values (42) 60
51.3%
2023-12-09T22:47:15.135326image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 50
24.9%
2 25
12.4%
6 24
11.9%
5 22
10.9%
4 16
 
8.0%
0 15
 
7.5%
9 14
 
7.0%
7 14
 
7.0%
3 13
 
6.5%
8 8
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 50
24.9%
2 25
12.4%
6 24
11.9%
5 22
10.9%
4 16
 
8.0%
0 15
 
7.5%
9 14
 
7.0%
7 14
 
7.0%
3 13
 
6.5%
8 8
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 201
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 50
24.9%
2 25
12.4%
6 24
11.9%
5 22
10.9%
4 16
 
8.0%
0 15
 
7.5%
9 14
 
7.0%
7 14
 
7.0%
3 13
 
6.5%
8 8
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 50
24.9%
2 25
12.4%
6 24
11.9%
5 22
10.9%
4 16
 
8.0%
0 15
 
7.5%
9 14
 
7.0%
7 14
 
7.0%
3 13
 
6.5%
8 8
 
4.0%

geseats_prog2
Text

MISSING 

Distinct74
Distinct (%)63.2%
Missing357
Missing (%)75.3%
Memory size18.1 KiB
2023-12-09T22:47:15.423208image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.316239316
Min length1

Characters and Unicode

Total characters271
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)46.2%

Sample

1st row66
2nd row24
3rd row193
4th row40
5th row245
ValueCountFrequency (%)
24 12
 
10.3%
49 7
 
6.0%
25 5
 
4.3%
48 4
 
3.4%
73 4
 
3.4%
193 3
 
2.6%
66 2
 
1.7%
75 2
 
1.7%
97 2
 
1.7%
30 2
 
1.7%
Other values (64) 74
63.2%
2023-12-09T22:47:15.840497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 44
16.2%
2 42
15.5%
1 33
12.2%
3 30
11.1%
9 26
9.6%
5 25
9.2%
7 21
7.7%
8 18
6.6%
6 16
 
5.9%
0 16
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 271
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 44
16.2%
2 42
15.5%
1 33
12.2%
3 30
11.1%
9 26
9.6%
5 25
9.2%
7 21
7.7%
8 18
6.6%
6 16
 
5.9%
0 16
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 271
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 44
16.2%
2 42
15.5%
1 33
12.2%
3 30
11.1%
9 26
9.6%
5 25
9.2%
7 21
7.7%
8 18
6.6%
6 16
 
5.9%
0 16
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 44
16.2%
2 42
15.5%
1 33
12.2%
3 30
11.1%
9 26
9.6%
5 25
9.2%
7 21
7.7%
8 18
6.6%
6 16
 
5.9%
0 16
 
5.9%

gefilled_prog2
Text

MISSING 

Distinct2
Distinct (%)1.7%
Missing357
Missing (%)75.3%
Memory size17.9 KiB
2023-12-09T22:47:15.956774image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters117
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowY
4th rowN
5th rowY
ValueCountFrequency (%)
n 81
69.2%
y 36
30.8%
2023-12-09T22:47:16.167932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 81
69.2%
Y 36
30.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 117
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 81
69.2%
Y 36
30.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 117
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 81
69.2%
Y 36
30.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 81
69.2%
Y 36
30.8%

swdfilled_prog2
Text

MISSING 

Distinct2
Distinct (%)1.7%
Missing357
Missing (%)75.3%
Memory size17.9 KiB
2023-12-09T22:47:16.271654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters117
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 71
60.7%
y 46
39.3%
2023-12-09T22:47:16.486397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 71
60.7%
Y 46
39.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 117
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 71
60.7%
Y 46
39.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 117
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 71
60.7%
Y 46
39.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 71
60.7%
Y 46
39.3%

eligibility_prog2
Text

MISSING 

Distinct32
Distinct (%)27.4%
Missing357
Missing (%)75.3%
Memory size23.0 KiB
2023-12-09T22:47:16.729916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length102
Median length89
Mean length45.70940171
Min length31

Characters and Unicode

Total characters5348
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)12.8%

Sample

1st rowOpen to students and residents of District 1
2nd rowOpen to students and residents of Manhattan
3rd rowOpen to students and residents of District 2
4th rowOpen to students and residents of District 2
5th rowOpen to students and residents of District 2
ValueCountFrequency (%)
students 125
13.0%
to 118
12.3%
open 117
12.2%
and 93
9.7%
residents 83
8.6%
of 82
8.5%
the 54
 
5.6%
district 46
 
4.8%
zone 33
 
3.4%
in 33
 
3.4%
Other values (45) 176
18.3%
2023-12-09T22:47:17.115913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
842
15.7%
t 628
11.7%
n 581
10.9%
e 553
10.3%
s 506
9.5%
d 345
 
6.5%
i 297
 
5.6%
o 293
 
5.5%
r 211
 
3.9%
u 134
 
2.5%
Other values (42) 958
17.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4141
77.4%
Space Separator 843
 
15.8%
Uppercase Letter 220
 
4.1%
Decimal Number 119
 
2.2%
Other Punctuation 18
 
0.3%
Control 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 628
15.2%
n 581
14.0%
e 553
13.4%
s 506
12.2%
d 345
8.3%
i 297
7.2%
o 293
7.1%
r 211
 
5.1%
u 134
 
3.2%
p 117
 
2.8%
Other values (12) 476
11.5%
Uppercase Letter
ValueCountFrequency (%)
O 117
53.2%
D 49
22.3%
B 31
 
14.1%
S 5
 
2.3%
à 4
 
1.8%
 4
 
1.8%
P 3
 
1.4%
I 2
 
0.9%
C 1
 
0.5%
Y 1
 
0.5%
Other values (3) 3
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 35
29.4%
1 31
26.1%
5 12
 
10.1%
3 9
 
7.6%
6 8
 
6.7%
0 7
 
5.9%
7 6
 
5.0%
4 5
 
4.2%
8 3
 
2.5%
9 3
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 10
55.6%
, 7
38.9%
& 1
 
5.6%
Space Separator
ValueCountFrequency (%)
842
99.9%
  1
 
0.1%
Control
ValueCountFrequency (%)
‚ 4
57.1%
ƒ 3
42.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 4361
81.5%
Common 987
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 628
14.4%
n 581
13.3%
e 553
12.7%
s 506
11.6%
d 345
7.9%
i 297
6.8%
o 293
6.7%
r 211
 
4.8%
u 134
 
3.1%
p 117
 
2.7%
Other values (25) 696
16.0%
Common
ValueCountFrequency (%)
842
85.3%
2 35
 
3.5%
1 31
 
3.1%
5 12
 
1.2%
. 10
 
1.0%
3 9
 
0.9%
6 8
 
0.8%
0 7
 
0.7%
, 7
 
0.7%
7 6
 
0.6%
Other values (7) 20
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5332
99.7%
None 16
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
842
15.8%
t 628
11.8%
n 581
10.9%
e 553
10.4%
s 506
9.5%
d 345
 
6.5%
i 297
 
5.6%
o 293
 
5.5%
r 211
 
4.0%
u 134
 
2.5%
Other values (37) 942
17.7%
None
ValueCountFrequency (%)
à 4
25.0%
 4
25.0%
‚ 4
25.0%
ƒ 3
18.8%
  1
 
6.2%

priority1_prog2
Text

MISSING 

Distinct15
Distinct (%)29.4%
Missing423
Missing (%)89.2%
Memory size18.5 KiB
2023-12-09T22:47:17.349133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length97
Median length96
Mean length46.84313725
Min length31

Characters and Unicode

Total characters2389
Distinct characters34
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)19.6%

Sample

1st rowPriority to continuing students
2nd rowPriority to students attending PS 8, PS 153, or PS 173 and to residents of the middle school zone
3rd rowPriority to students attending PS 5, PS 48, or PS 152 and to residents of the middle school zone
4th rowPriority to students attending PS 4, PS 28, or PS 128 and to residents of the middle school zone
5th rowPriority to District 7 students and residents
ValueCountFrequency (%)
to 55
13.9%
priority 51
12.9%
residents 40
10.1%
students 28
 
7.1%
of 27
 
6.8%
the 26
 
6.6%
zone 26
 
6.6%
middle 25
 
6.3%
school 25
 
6.3%
and 17
 
4.3%
Other values (27) 75
19.0%
2023-12-09T22:47:17.719726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
14.4%
t 274
11.5%
o 225
9.4%
i 219
9.2%
e 190
8.0%
s 174
 
7.3%
r 160
 
6.7%
n 150
 
6.3%
d 140
 
5.9%
P 64
 
2.7%
Other values (24) 449
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1885
78.9%
Space Separator 344
 
14.4%
Uppercase Letter 94
 
3.9%
Decimal Number 57
 
2.4%
Other Punctuation 9
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 274
14.5%
o 225
11.9%
i 219
11.6%
e 190
10.1%
s 174
9.2%
r 160
8.5%
n 150
8.0%
d 140
7.4%
y 51
 
2.7%
h 51
 
2.7%
Other values (8) 251
13.3%
Decimal Number
ValueCountFrequency (%)
1 22
38.6%
7 6
 
10.5%
4 6
 
10.5%
0 5
 
8.8%
8 5
 
8.8%
2 4
 
7.0%
5 4
 
7.0%
3 3
 
5.3%
9 2
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
P 64
68.1%
S 14
 
14.9%
D 14
 
14.9%
X 1
 
1.1%
R 1
 
1.1%
Space Separator
ValueCountFrequency (%)
344
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1979
82.8%
Common 410
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 274
13.8%
o 225
11.4%
i 219
11.1%
e 190
9.6%
s 174
8.8%
r 160
8.1%
n 150
7.6%
d 140
7.1%
P 64
 
3.2%
y 51
 
2.6%
Other values (13) 332
16.8%
Common
ValueCountFrequency (%)
344
83.9%
1 22
 
5.4%
, 9
 
2.2%
7 6
 
1.5%
4 6
 
1.5%
0 5
 
1.2%
8 5
 
1.2%
2 4
 
1.0%
5 4
 
1.0%
3 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
344
14.4%
t 274
11.5%
o 225
9.4%
i 219
9.2%
e 190
8.0%
s 174
 
7.3%
r 160
 
6.7%
n 150
 
6.3%
d 140
 
5.9%
P 64
 
2.7%
Other values (24) 449
18.8%

priority2_prog2
Text

MISSING 

Distinct16
Distinct (%)32.7%
Missing425
Missing (%)89.7%
Memory size18.1 KiB
2023-12-09T22:47:17.926810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length46
Mean length41.24489796
Min length36

Characters and Unicode

Total characters2021
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)12.2%

Sample

1st rowThen to residents of the elementary school zone
2nd rowThen to District 6 students and residents
3rd rowThen to District 6 students and residents
4th rowThen to District 6 students and residents
5th rowThen to Bronx students and residents
ValueCountFrequency (%)
residents 49
14.5%
to 49
14.5%
then 48
14.2%
students 40
11.8%
and 40
11.8%
district 27
8.0%
bronx 10
 
2.9%
of 9
 
2.7%
the 9
 
2.7%
school 9
 
2.7%
Other values (16) 49
14.5%
2023-12-09T22:47:18.601934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
14.3%
t 248
12.3%
e 225
11.1%
s 214
10.6%
n 205
10.1%
d 135
6.7%
i 108
 
5.3%
o 102
 
5.0%
r 97
 
4.8%
h 66
 
3.3%
Other values (22) 331
16.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1593
78.8%
Space Separator 290
 
14.3%
Uppercase Letter 89
 
4.4%
Decimal Number 49
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 248
15.6%
e 225
14.1%
s 214
13.4%
n 205
12.9%
d 135
8.5%
i 108
6.8%
o 102
6.4%
r 97
 
6.1%
h 66
 
4.1%
a 46
 
2.9%
Other values (9) 147
9.2%
Decimal Number
ValueCountFrequency (%)
1 15
30.6%
2 12
24.5%
0 7
14.3%
8 5
 
10.2%
7 4
 
8.2%
6 3
 
6.1%
9 2
 
4.1%
5 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
T 48
53.9%
D 27
30.3%
B 13
 
14.6%
P 1
 
1.1%
Space Separator
ValueCountFrequency (%)
290
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1682
83.2%
Common 339
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 248
14.7%
e 225
13.4%
s 214
12.7%
n 205
12.2%
d 135
8.0%
i 108
6.4%
o 102
6.1%
r 97
 
5.8%
h 66
 
3.9%
T 48
 
2.9%
Other values (13) 234
13.9%
Common
ValueCountFrequency (%)
290
85.5%
1 15
 
4.4%
2 12
 
3.5%
0 7
 
2.1%
8 5
 
1.5%
7 4
 
1.2%
6 3
 
0.9%
9 2
 
0.6%
5 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290
14.3%
t 248
12.3%
e 225
11.1%
s 214
10.6%
n 205
10.1%
d 135
6.7%
i 108
 
5.3%
o 102
 
5.0%
r 97
 
4.8%
h 66
 
3.3%
Other values (22) 331
16.4%

priority3_prog2
Text

MISSING 

Distinct3
Distinct (%)25.0%
Missing462
Missing (%)97.5%
Memory size15.7 KiB
2023-12-09T22:47:18.792875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length36
Mean length36.91666667
Min length36

Characters and Unicode

Total characters443
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st rowThen to District 4 students and residents
2nd rowThen to Bronx students and residents
3rd rowThen to Bronx students and residents
4th rowThen to Bronx students and residents
5th rowThen to Bronx students and residents
ValueCountFrequency (%)
then 12
16.2%
to 12
16.2%
students 12
16.2%
and 12
16.2%
residents 12
16.2%
bronx 10
13.5%
district 2
 
2.7%
11 1
 
1.4%
4 1
 
1.4%
2023-12-09T22:47:19.109241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
14.0%
n 58
13.1%
t 52
11.7%
s 50
11.3%
e 48
10.8%
d 36
8.1%
r 24
 
5.4%
o 22
 
5.0%
i 16
 
3.6%
T 12
 
2.7%
Other values (9) 63
14.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 354
79.9%
Space Separator 62
 
14.0%
Uppercase Letter 24
 
5.4%
Decimal Number 3
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 58
16.4%
t 52
14.7%
s 50
14.1%
e 48
13.6%
d 36
10.2%
r 24
6.8%
o 22
 
6.2%
i 16
 
4.5%
a 12
 
3.4%
h 12
 
3.4%
Other values (3) 24
6.8%
Uppercase Letter
ValueCountFrequency (%)
T 12
50.0%
B 10
41.7%
D 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 378
85.3%
Common 65
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 58
15.3%
t 52
13.8%
s 50
13.2%
e 48
12.7%
d 36
9.5%
r 24
6.3%
o 22
 
5.8%
i 16
 
4.2%
T 12
 
3.2%
a 12
 
3.2%
Other values (6) 48
12.7%
Common
ValueCountFrequency (%)
62
95.4%
1 2
 
3.1%
4 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
14.0%
n 58
13.1%
t 52
11.7%
s 50
11.3%
e 48
10.8%
d 36
8.1%
r 24
 
5.4%
o 22
 
5.0%
i 16
 
3.6%
T 12
 
2.7%
Other values (9) 63
14.2%

priority4_prog2
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:47:19.295569image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters36
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to Bronx students and residents
ValueCountFrequency (%)
then 1
16.7%
to 1
16.7%
bronx 1
16.7%
students 1
16.7%
and 1
16.7%
residents 1
16.7%
2023-12-09T22:47:19.591478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 5
13.9%
5
13.9%
e 4
11.1%
t 4
11.1%
s 4
11.1%
d 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
T 1
 
2.8%
h 1
 
2.8%
Other values (5) 5
13.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29
80.6%
Space Separator 5
 
13.9%
Uppercase Letter 2
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 5
17.2%
e 4
13.8%
t 4
13.8%
s 4
13.8%
d 3
10.3%
o 2
 
6.9%
r 2
 
6.9%
h 1
 
3.4%
x 1
 
3.4%
u 1
 
3.4%
Other values (2) 2
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31
86.1%
Common 5
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 5
16.1%
e 4
12.9%
t 4
12.9%
s 4
12.9%
d 3
9.7%
o 2
 
6.5%
r 2
 
6.5%
T 1
 
3.2%
h 1
 
3.2%
B 1
 
3.2%
Other values (4) 4
12.9%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 5
13.9%
5
13.9%
e 4
11.1%
t 4
11.1%
s 4
11.1%
d 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
T 1
 
2.8%
h 1
 
2.8%
Other values (5) 5
13.9%

priority5_prog2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog3
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing441
Missing (%)93.0%
Memory size15.9 KiB
2023-12-09T22:47:19.833506image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.181818182
Min length5

Characters and Unicode

Total characters171
Distinct characters25
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st rowM131P
2nd rowX118Z
3rd rowX368Z
4th rowX390Z
5th rowX127Z
ValueCountFrequency (%)
k218z 1
 
3.0%
q073u 1
 
3.0%
k098cm 1
 
3.0%
q204z 1
 
3.0%
x180u 1
 
3.0%
q077z 1
 
3.0%
k096jo 1
 
3.0%
k136s 1
 
3.0%
k180z 1
 
3.0%
q126z 1
 
3.0%
Other values (23) 23
69.7%
2023-12-09T22:47:20.201528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
11.1%
0 18
10.5%
Z 17
9.9%
K 16
 
9.4%
2 14
 
8.2%
8 12
 
7.0%
3 11
 
6.4%
6 8
 
4.7%
Q 7
 
4.1%
X 7
 
4.1%
Other values (15) 42
24.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99
57.9%
Uppercase Letter 72
42.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Z 17
23.6%
K 16
22.2%
Q 7
9.7%
X 7
9.7%
U 5
 
6.9%
M 4
 
5.6%
C 3
 
4.2%
D 3
 
4.2%
R 2
 
2.8%
A 2
 
2.8%
Other values (5) 6
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 19
19.2%
0 18
18.2%
2 14
14.1%
8 12
12.1%
3 11
11.1%
6 8
8.1%
7 7
 
7.1%
9 5
 
5.1%
4 3
 
3.0%
5 2
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99
57.9%
Latin 72
42.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 17
23.6%
K 16
22.2%
Q 7
9.7%
X 7
9.7%
U 5
 
6.9%
M 4
 
5.6%
C 3
 
4.2%
D 3
 
4.2%
R 2
 
2.8%
A 2
 
2.8%
Other values (5) 6
 
8.3%
Common
ValueCountFrequency (%)
1 19
19.2%
0 18
18.2%
2 14
14.1%
8 12
12.1%
3 11
11.1%
6 8
8.1%
7 7
 
7.1%
9 5
 
5.1%
4 3
 
3.0%
5 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
11.1%
0 18
10.5%
Z 17
9.9%
K 16
 
9.4%
2 14
 
8.2%
8 12
 
7.0%
3 11
 
6.4%
6 8
 
4.7%
Q 7
 
4.1%
X 7
 
4.1%
Other values (15) 42
24.6%

name_prog3
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing441
Missing (%)93.0%
Memory size16.8 KiB
2023-12-09T22:47:20.522382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length64
Median length45
Mean length33.09090909
Min length7

Characters and Unicode

Total characters1092
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)84.8%

Sample

1st rowM.S. 131 Mandarin Dual Language Program
2nd rowAcademy of Excellence
3rd rowZoned Program
4th rowM.S. 390 Zoned Program
5th rowCastle Hill Middle School 127 Zoned Program
ValueCountFrequency (%)
program 22
 
12.9%
zoned 15
 
8.8%
i.s 15
 
8.8%
magnet 6
 
3.5%
academy 6
 
3.5%
school 6
 
3.5%
the 5
 
2.9%
of 3
 
1.8%
computer/math 3
 
1.8%
middle 3
 
1.8%
Other values (80) 86
50.6%
2023-12-09T22:47:20.994142image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
 
12.5%
e 84
 
7.7%
r 73
 
6.7%
a 73
 
6.7%
o 70
 
6.4%
. 45
 
4.1%
n 44
 
4.0%
d 39
 
3.6%
m 37
 
3.4%
l 35
 
3.2%
Other values (48) 455
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 644
59.0%
Uppercase Letter 173
 
15.8%
Space Separator 137
 
12.5%
Other Punctuation 51
 
4.7%
Decimal Number 51
 
4.7%
Open Punctuation 18
 
1.6%
Close Punctuation 18
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 84
13.0%
r 73
11.3%
a 73
11.3%
o 70
10.9%
n 44
 
6.8%
d 39
 
6.1%
m 37
 
5.7%
l 35
 
5.4%
g 34
 
5.3%
t 27
 
4.2%
Other values (13) 128
19.9%
Uppercase Letter
ValueCountFrequency (%)
S 29
16.8%
P 25
14.5%
M 18
10.4%
I 17
9.8%
Z 15
8.7%
A 10
 
5.8%
C 9
 
5.2%
D 8
 
4.6%
H 7
 
4.0%
L 7
 
4.0%
Other values (10) 28
16.2%
Decimal Number
ValueCountFrequency (%)
1 9
17.6%
8 8
15.7%
3 8
15.7%
2 7
13.7%
9 5
9.8%
7 5
9.8%
6 4
7.8%
0 3
 
5.9%
5 2
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 45
88.2%
/ 4
 
7.8%
: 2
 
3.9%
Space Separator
ValueCountFrequency (%)
137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 817
74.8%
Common 275
 
25.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 84
 
10.3%
r 73
 
8.9%
a 73
 
8.9%
o 70
 
8.6%
n 44
 
5.4%
d 39
 
4.8%
m 37
 
4.5%
l 35
 
4.3%
g 34
 
4.2%
S 29
 
3.5%
Other values (33) 299
36.6%
Common
ValueCountFrequency (%)
137
49.8%
. 45
 
16.4%
( 18
 
6.5%
) 18
 
6.5%
1 9
 
3.3%
8 8
 
2.9%
3 8
 
2.9%
2 7
 
2.5%
9 5
 
1.8%
7 5
 
1.8%
Other values (5) 15
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
 
12.5%
e 84
 
7.7%
r 73
 
6.7%
a 73
 
6.7%
o 70
 
6.4%
. 45
 
4.1%
n 44
 
4.0%
d 39
 
3.6%
m 37
 
3.4%
l 35
 
3.2%
Other values (48) 455
41.7%

admissionsmethod_prog3
Text

MISSING 

Distinct6
Distinct (%)18.2%
Missing441
Missing (%)93.0%
Memory size16.0 KiB
2023-12-09T22:47:21.167957image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length5
Mean length6.666666667
Min length4

Characters and Unicode

Total characters220
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.1%

Sample

1st rowScreened: Language
2nd rowZoned
3rd rowZoned
4th rowZoned
5th rowZoned
ValueCountFrequency (%)
zoned 17
41.5%
open 7
17.1%
talent 6
 
14.6%
test 6
 
14.6%
screened 2
 
4.9%
composite 1
 
2.4%
score 1
 
2.4%
language 1
 
2.4%
2023-12-09T22:47:21.466733image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 45
20.5%
n 33
15.0%
o 20
9.1%
d 19
8.6%
Z 17
 
7.7%
t 13
 
5.9%
T 12
 
5.5%
a 8
 
3.6%
8
 
3.6%
p 8
 
3.6%
Other values (13) 37
16.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 170
77.3%
Uppercase Letter 41
 
18.6%
Space Separator 8
 
3.6%
Other Punctuation 1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 45
26.5%
n 33
19.4%
o 20
11.8%
d 19
11.2%
t 13
 
7.6%
a 8
 
4.7%
p 8
 
4.7%
s 7
 
4.1%
l 6
 
3.5%
c 3
 
1.8%
Other values (5) 8
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
Z 17
41.5%
T 12
29.3%
O 7
17.1%
S 3
 
7.3%
C 1
 
2.4%
L 1
 
2.4%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 211
95.9%
Common 9
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 45
21.3%
n 33
15.6%
o 20
9.5%
d 19
9.0%
Z 17
 
8.1%
t 13
 
6.2%
T 12
 
5.7%
a 8
 
3.8%
p 8
 
3.8%
O 7
 
3.3%
Other values (11) 29
13.7%
Common
ValueCountFrequency (%)
8
88.9%
: 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 45
20.5%
n 33
15.0%
o 20
9.1%
d 19
8.6%
Z 17
 
7.7%
t 13
 
5.9%
T 12
 
5.5%
a 8
 
3.6%
8
 
3.6%
p 8
 
3.6%
Other values (13) 37
16.8%

geapps_prog3
Text

MISSING 

Distinct32
Distinct (%)97.0%
Missing441
Missing (%)93.0%
Memory size15.8 KiB
2023-12-09T22:47:21.687808image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.757575758
Min length2

Characters and Unicode

Total characters91
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)93.9%

Sample

1st row92
2nd row229
3rd row143
4th row143
5th row149
ValueCountFrequency (%)
143 2
 
6.1%
167 1
 
3.0%
229 1
 
3.0%
639 1
 
3.0%
464 1
 
3.0%
114 1
 
3.0%
1035 1
 
3.0%
92 1
 
3.0%
30 1
 
3.0%
583 1
 
3.0%
Other values (22) 22
66.7%
2023-12-09T22:47:22.039135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
18.7%
3 14
15.4%
4 10
11.0%
2 10
11.0%
6 9
9.9%
9 9
9.9%
5 9
9.9%
0 5
 
5.5%
8 5
 
5.5%
7 3
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
18.7%
3 14
15.4%
4 10
11.0%
2 10
11.0%
6 9
9.9%
9 9
9.9%
5 9
9.9%
0 5
 
5.5%
8 5
 
5.5%
7 3
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 91
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
18.7%
3 14
15.4%
4 10
11.0%
2 10
11.0%
6 9
9.9%
9 9
9.9%
5 9
9.9%
0 5
 
5.5%
8 5
 
5.5%
7 3
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
18.7%
3 14
15.4%
4 10
11.0%
2 10
11.0%
6 9
9.9%
9 9
9.9%
5 9
9.9%
0 5
 
5.5%
8 5
 
5.5%
7 3
 
3.3%

swdapps_prog3
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing441
Missing (%)93.0%
Memory size15.8 KiB
2023-12-09T22:47:22.271804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row18
2nd row58
3rd row37
4th row37
5th row34
ValueCountFrequency (%)
15 2
 
6.1%
7 2
 
6.1%
44 2
 
6.1%
37 2
 
6.1%
34 2
 
6.1%
31 1
 
3.0%
22 1
 
3.0%
73 1
 
3.0%
18 1
 
3.0%
35 1
 
3.0%
Other values (18) 18
54.5%
2023-12-09T22:47:22.625451image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.2%
3 12
18.2%
7 8
12.1%
5 7
10.6%
4 7
10.6%
2 6
9.1%
6 5
 
7.6%
9 3
 
4.5%
8 3
 
4.5%
0 1
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.2%
3 12
18.2%
7 8
12.1%
5 7
10.6%
4 7
10.6%
2 6
9.1%
6 5
 
7.6%
9 3
 
4.5%
8 3
 
4.5%
0 1
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 66
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
21.2%
3 12
18.2%
7 8
12.1%
5 7
10.6%
4 7
10.6%
2 6
9.1%
6 5
 
7.6%
9 3
 
4.5%
8 3
 
4.5%
0 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
21.2%
3 12
18.2%
7 8
12.1%
5 7
10.6%
4 7
10.6%
2 6
9.1%
6 5
 
7.6%
9 3
 
4.5%
8 3
 
4.5%
0 1
 
1.5%

geappsperseat_prog3
Text

MISSING 

Distinct11
Distinct (%)33.3%
Missing441
Missing (%)93.0%
Memory size15.8 KiB
2023-12-09T22:47:22.764583image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.090909091
Min length1

Characters and Unicode

Total characters36
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)21.2%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2
ValueCountFrequency (%)
1 11
33.3%
2 10
30.3%
4 3
 
9.1%
3 2
 
6.1%
12 1
 
3.0%
22 1
 
3.0%
7 1
 
3.0%
6 1
 
3.0%
5 1
 
3.0%
13 1
 
3.0%
2023-12-09T22:47:23.013323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
36.1%
2 13
36.1%
4 3
 
8.3%
3 3
 
8.3%
7 1
 
2.8%
6 1
 
2.8%
5 1
 
2.8%
8 1
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
36.1%
2 13
36.1%
4 3
 
8.3%
3 3
 
8.3%
7 1
 
2.8%
6 1
 
2.8%
5 1
 
2.8%
8 1
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 36
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
36.1%
2 13
36.1%
4 3
 
8.3%
3 3
 
8.3%
7 1
 
2.8%
6 1
 
2.8%
5 1
 
2.8%
8 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
36.1%
2 13
36.1%
4 3
 
8.3%
3 3
 
8.3%
7 1
 
2.8%
6 1
 
2.8%
5 1
 
2.8%
8 1
 
2.8%

swdappsperseat_prog3
Text

MISSING 

Distinct8
Distinct (%)24.2%
Missing441
Missing (%)93.0%
Memory size15.8 KiB
2023-12-09T22:47:23.131847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters33
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)6.1%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row1
ValueCountFrequency (%)
1 11
33.3%
2 7
21.2%
3 5
15.2%
5 4
 
12.1%
0 2
 
6.1%
6 2
 
6.1%
9 1
 
3.0%
4 1
 
3.0%
2023-12-09T22:47:23.362948image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
33.3%
2 7
21.2%
3 5
15.2%
5 4
 
12.1%
0 2
 
6.1%
6 2
 
6.1%
9 1
 
3.0%
4 1
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
33.3%
2 7
21.2%
3 5
15.2%
5 4
 
12.1%
0 2
 
6.1%
6 2
 
6.1%
9 1
 
3.0%
4 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
33.3%
2 7
21.2%
3 5
15.2%
5 4
 
12.1%
0 2
 
6.1%
6 2
 
6.1%
9 1
 
3.0%
4 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
33.3%
2 7
21.2%
3 5
15.2%
5 4
 
12.1%
0 2
 
6.1%
6 2
 
6.1%
9 1
 
3.0%
4 1
 
3.0%

swdseats_prog3
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing441
Missing (%)93.0%
Memory size15.8 KiB
2023-12-09T22:47:23.564848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.787878788
Min length1

Characters and Unicode

Total characters59
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)33.3%

Sample

1st row13
2nd row25
3rd row22
4th row23
5th row23
ValueCountFrequency (%)
15 3
 
9.1%
23 3
 
9.1%
22 2
 
6.1%
13 2
 
6.1%
10 2
 
6.1%
6 2
 
6.1%
5 2
 
6.1%
54 2
 
6.1%
30 2
 
6.1%
4 2
 
6.1%
Other values (11) 11
33.3%
2023-12-09T22:47:23.879481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
18.6%
1 10
16.9%
5 9
15.3%
3 8
13.6%
4 6
10.2%
0 5
8.5%
9 4
 
6.8%
6 3
 
5.1%
7 2
 
3.4%
8 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
18.6%
1 10
16.9%
5 9
15.3%
3 8
13.6%
4 6
10.2%
0 5
8.5%
9 4
 
6.8%
6 3
 
5.1%
7 2
 
3.4%
8 1
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 59
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
18.6%
1 10
16.9%
5 9
15.3%
3 8
13.6%
4 6
10.2%
0 5
8.5%
9 4
 
6.8%
6 3
 
5.1%
7 2
 
3.4%
8 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
18.6%
1 10
16.9%
5 9
15.3%
3 8
13.6%
4 6
10.2%
0 5
8.5%
9 4
 
6.8%
6 3
 
5.1%
7 2
 
3.4%
8 1
 
1.7%

geseats_prog3
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing441
Missing (%)93.0%
Memory size15.8 KiB
2023-12-09T22:47:24.088377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.303030303
Min length2

Characters and Unicode

Total characters76
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row47
2nd row95
3rd row84
4th row87
5th row97
ValueCountFrequency (%)
24 4
 
12.1%
75 3
 
9.1%
77 2
 
6.1%
20 1
 
3.0%
90 1
 
3.0%
384 1
 
3.0%
76 1
 
3.0%
122 1
 
3.0%
162 1
 
3.0%
97 1
 
3.0%
Other values (17) 17
51.5%
2023-12-09T22:47:24.418413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
18.4%
7 12
15.8%
6 9
11.8%
4 8
10.5%
1 8
10.5%
5 6
7.9%
0 6
7.9%
9 5
 
6.6%
3 4
 
5.3%
8 4
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
18.4%
7 12
15.8%
6 9
11.8%
4 8
10.5%
1 8
10.5%
5 6
7.9%
0 6
7.9%
9 5
 
6.6%
3 4
 
5.3%
8 4
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 76
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
18.4%
7 12
15.8%
6 9
11.8%
4 8
10.5%
1 8
10.5%
5 6
7.9%
0 6
7.9%
9 5
 
6.6%
3 4
 
5.3%
8 4
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
18.4%
7 12
15.8%
6 9
11.8%
4 8
10.5%
1 8
10.5%
5 6
7.9%
0 6
7.9%
9 5
 
6.6%
3 4
 
5.3%
8 4
 
5.3%

gefilled_prog3
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing441
Missing (%)93.0%
Memory size15.9 KiB
2023-12-09T22:47:24.565248image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.727272727
Min length4

Characters and Unicode

Total characters156
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfalse
2nd rowfalse
3rd rowfalse
4th rowfalse
5th rowfalse
ValueCountFrequency (%)
false 24
72.7%
true 9
 
27.3%
2023-12-09T22:47:24.817221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 33
21.2%
f 24
15.4%
a 24
15.4%
l 24
15.4%
s 24
15.4%
t 9
 
5.8%
r 9
 
5.8%
u 9
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 156
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 33
21.2%
f 24
15.4%
a 24
15.4%
l 24
15.4%
s 24
15.4%
t 9
 
5.8%
r 9
 
5.8%
u 9
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 156
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 33
21.2%
f 24
15.4%
a 24
15.4%
l 24
15.4%
s 24
15.4%
t 9
 
5.8%
r 9
 
5.8%
u 9
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 33
21.2%
f 24
15.4%
a 24
15.4%
l 24
15.4%
s 24
15.4%
t 9
 
5.8%
r 9
 
5.8%
u 9
 
5.8%

swdfilled_prog3
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing441
Missing (%)93.0%
Memory size15.9 KiB
2023-12-09T22:47:24.957194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.606060606
Min length4

Characters and Unicode

Total characters152
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfalse
2nd rowfalse
3rd rowfalse
4th rowfalse
5th rowfalse
ValueCountFrequency (%)
false 20
60.6%
true 13
39.4%
2023-12-09T22:47:25.211912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 33
21.7%
f 20
13.2%
a 20
13.2%
l 20
13.2%
s 20
13.2%
t 13
 
8.6%
r 13
 
8.6%
u 13
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 152
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 33
21.7%
f 20
13.2%
a 20
13.2%
l 20
13.2%
s 20
13.2%
t 13
 
8.6%
r 13
 
8.6%
u 13
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 152
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 33
21.7%
f 20
13.2%
a 20
13.2%
l 20
13.2%
s 20
13.2%
t 13
 
8.6%
r 13
 
8.6%
u 13
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 33
21.7%
f 20
13.2%
a 20
13.2%
l 20
13.2%
s 20
13.2%
t 13
 
8.6%
r 13
 
8.6%
u 13
 
8.6%

eligibility_prog3
Text

MISSING 

Distinct12
Distinct (%)36.4%
Missing441
Missing (%)93.0%
Memory size17.2 KiB
2023-12-09T22:47:25.432345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length102
Median length89
Mean length44.12121212
Min length31

Characters and Unicode

Total characters1456
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)24.2%

Sample

1st rowOpen to students and residents of Manhattan
2nd rowOpen to students and residents of the Bronx
3rd rowOpen to students and residents of the Bronx
4th rowOpen to students and residents of the Bronx
5th rowOpen to students residing in the zone
ValueCountFrequency (%)
students 34
12.7%
to 34
12.7%
open 33
12.3%
and 20
 
7.5%
the 19
 
7.1%
residents 18
 
6.7%
of 17
 
6.3%
residing 14
 
5.2%
in 14
 
5.2%
zone 14
 
5.2%
Other values (27) 51
19.0%
2023-12-09T22:47:25.788440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
235
16.1%
t 169
11.6%
n 159
10.9%
e 157
10.8%
s 130
8.9%
d 89
 
6.1%
i 85
 
5.8%
o 76
 
5.2%
r 53
 
3.6%
u 35
 
2.4%
Other values (35) 268
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1110
76.2%
Space Separator 235
 
16.1%
Uppercase Letter 63
 
4.3%
Decimal Number 36
 
2.5%
Other Punctuation 12
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 169
15.2%
n 159
14.3%
e 157
14.1%
s 130
11.7%
d 89
8.0%
i 85
7.7%
o 76
6.8%
r 53
 
4.8%
u 35
 
3.2%
p 33
 
3.0%
Other values (12) 124
11.2%
Uppercase Letter
ValueCountFrequency (%)
O 33
52.4%
D 11
 
17.5%
B 5
 
7.9%
S 5
 
7.9%
P 3
 
4.8%
I 2
 
3.2%
M 1
 
1.6%
N 1
 
1.6%
Y 1
 
1.6%
C 1
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 15
41.7%
2 7
19.4%
5 3
 
8.3%
3 3
 
8.3%
6 2
 
5.6%
0 2
 
5.6%
8 1
 
2.8%
9 1
 
2.8%
4 1
 
2.8%
7 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 10
83.3%
, 2
 
16.7%
Space Separator
ValueCountFrequency (%)
235
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1173
80.6%
Common 283
 
19.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 169
14.4%
n 159
13.6%
e 157
13.4%
s 130
11.1%
d 89
7.6%
i 85
7.2%
o 76
6.5%
r 53
 
4.5%
u 35
 
3.0%
O 33
 
2.8%
Other values (22) 187
15.9%
Common
ValueCountFrequency (%)
235
83.0%
1 15
 
5.3%
. 10
 
3.5%
2 7
 
2.5%
5 3
 
1.1%
3 3
 
1.1%
, 2
 
0.7%
6 2
 
0.7%
0 2
 
0.7%
8 1
 
0.4%
Other values (3) 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
235
16.1%
t 169
11.6%
n 159
10.9%
e 157
10.8%
s 130
8.9%
d 89
 
6.1%
i 85
 
5.8%
o 76
 
5.2%
r 53
 
3.6%
u 35
 
2.4%
Other values (35) 268
18.4%

priority1_prog3
Text

MISSING 

Distinct2
Distinct (%)25.0%
Missing466
Missing (%)98.3%
Memory size15.5 KiB
2023-12-09T22:47:25.987334image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length45
Min length31

Characters and Unicode

Total characters360
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)12.5%

Sample

1st rowPriority to residents of the middle school zone
2nd rowPriority to residents of the middle school zone
3rd rowPriority to residents of the middle school zone
4th rowPriority to residents of the middle school zone
5th rowPriority to residents of the middle school zone
ValueCountFrequency (%)
priority 8
13.3%
to 8
13.3%
residents 7
11.7%
of 7
11.7%
the 7
11.7%
middle 7
11.7%
school 7
11.7%
zone 7
11.7%
continuing 1
 
1.7%
students 1
 
1.7%
2023-12-09T22:47:26.307955image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
14.4%
o 45
12.5%
e 36
10.0%
t 33
9.2%
i 32
8.9%
s 23
 
6.4%
r 23
 
6.4%
d 22
 
6.1%
n 18
 
5.0%
h 14
 
3.9%
Other values (9) 62
17.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 300
83.3%
Space Separator 52
 
14.4%
Uppercase Letter 8
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 45
15.0%
e 36
12.0%
t 33
11.0%
i 32
10.7%
s 23
7.7%
r 23
7.7%
d 22
7.3%
n 18
 
6.0%
h 14
 
4.7%
l 14
 
4.7%
Other values (7) 40
13.3%
Space Separator
ValueCountFrequency (%)
52
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 308
85.6%
Common 52
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 45
14.6%
e 36
11.7%
t 33
10.7%
i 32
10.4%
s 23
7.5%
r 23
7.5%
d 22
7.1%
n 18
 
5.8%
h 14
 
4.5%
l 14
 
4.5%
Other values (8) 48
15.6%
Common
ValueCountFrequency (%)
52
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
14.4%
o 45
12.5%
e 36
10.0%
t 33
9.2%
i 32
8.9%
s 23
 
6.4%
r 23
 
6.4%
d 22
 
6.1%
n 18
 
5.0%
h 14
 
3.9%
Other values (9) 62
17.2%

priority2_prog3
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing466
Missing (%)98.3%
Memory size15.5 KiB
2023-12-09T22:47:26.514575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length42
Mean length42.625
Min length42

Characters and Unicode

Total characters341
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)37.5%

Sample

1st rowThen to District 10 students and residents
2nd rowThen to District 10 students and residents
3rd rowThen to District 10 students and residents
4th rowThen to District 11 students and residents
5th rowThen to District 11 students and residents
ValueCountFrequency (%)
then 8
14.0%
to 8
14.0%
residents 8
14.0%
district 7
12.3%
students 7
12.3%
and 7
12.3%
10 3
 
5.3%
11 2
 
3.5%
17 1
 
1.8%
of 1
 
1.8%
Other values (5) 5
8.8%
2023-12-09T22:47:26.839688image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
14.4%
t 46
13.5%
s 38
11.1%
e 36
10.6%
n 32
9.4%
i 22
 
6.5%
d 22
 
6.5%
r 16
 
4.7%
o 12
 
3.5%
h 10
 
2.9%
Other values (14) 58
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 263
77.1%
Space Separator 49
 
14.4%
Uppercase Letter 15
 
4.4%
Decimal Number 14
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 46
17.5%
s 38
14.4%
e 36
13.7%
n 32
12.2%
i 22
8.4%
d 22
8.4%
r 16
 
6.1%
o 12
 
4.6%
h 10
 
3.8%
a 8
 
3.0%
Other values (7) 21
8.0%
Decimal Number
ValueCountFrequency (%)
1 9
64.3%
0 3
 
21.4%
7 1
 
7.1%
8 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
T 8
53.3%
D 7
46.7%
Space Separator
ValueCountFrequency (%)
49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 278
81.5%
Common 63
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 46
16.5%
s 38
13.7%
e 36
12.9%
n 32
11.5%
i 22
7.9%
d 22
7.9%
r 16
 
5.8%
o 12
 
4.3%
h 10
 
3.6%
a 8
 
2.9%
Other values (9) 36
12.9%
Common
ValueCountFrequency (%)
49
77.8%
1 9
 
14.3%
0 3
 
4.8%
7 1
 
1.6%
8 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 341
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49
14.4%
t 46
13.5%
s 38
11.1%
e 36
10.6%
n 32
9.4%
i 22
 
6.5%
d 22
 
6.5%
r 16
 
4.7%
o 12
 
3.5%
h 10
 
2.9%
Other values (14) 58
17.0%

priority3_prog3
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)20.0%
Missing469
Missing (%)98.9%
Memory size15.2 KiB
2023-12-09T22:47:27.021558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters180
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThen to Bronx students and residents
2nd rowThen to Bronx students and residents
3rd rowThen to Bronx students and residents
4th rowThen to Bronx students and residents
5th rowThen to Bronx students and residents
ValueCountFrequency (%)
then 5
16.7%
to 5
16.7%
bronx 5
16.7%
students 5
16.7%
and 5
16.7%
residents 5
16.7%
2023-12-09T22:47:27.319078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 25
13.9%
25
13.9%
e 20
11.1%
t 20
11.1%
s 20
11.1%
d 15
8.3%
o 10
 
5.6%
r 10
 
5.6%
T 5
 
2.8%
h 5
 
2.8%
Other values (5) 25
13.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 145
80.6%
Space Separator 25
 
13.9%
Uppercase Letter 10
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 25
17.2%
e 20
13.8%
t 20
13.8%
s 20
13.8%
d 15
10.3%
o 10
 
6.9%
r 10
 
6.9%
h 5
 
3.4%
x 5
 
3.4%
u 5
 
3.4%
Other values (2) 10
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
T 5
50.0%
B 5
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 155
86.1%
Common 25
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 25
16.1%
e 20
12.9%
t 20
12.9%
s 20
12.9%
d 15
9.7%
o 10
 
6.5%
r 10
 
6.5%
T 5
 
3.2%
h 5
 
3.2%
B 5
 
3.2%
Other values (4) 20
12.9%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 25
13.9%
25
13.9%
e 20
11.1%
t 20
11.1%
s 20
11.1%
d 15
8.3%
o 10
 
5.6%
r 10
 
5.6%
T 5
 
2.8%
h 5
 
2.8%
Other values (5) 25
13.9%

priority4_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog4
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:27.510338image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.6
Min length5

Characters and Unicode

Total characters56
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st rowX144Z
2nd rowK113T
3rd rowK220Z
4th rowK096SC
5th rowK098DA
ValueCountFrequency (%)
x144z 1
10.0%
k113t 1
10.0%
k239da 1
10.0%
k220z 1
10.0%
k096sc 1
10.0%
q073z 1
10.0%
k228da 1
10.0%
k303dr 1
10.0%
k281jo 1
10.0%
k098da 1
10.0%
2023-12-09T22:47:27.878584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 8
14.3%
2 6
10.7%
3 5
8.9%
0 5
8.9%
D 4
 
7.1%
1 4
 
7.1%
A 3
 
5.4%
Z 3
 
5.4%
9 3
 
5.4%
8 3
 
5.4%
Other values (11) 12
21.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
53.6%
Uppercase Letter 26
46.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 8
30.8%
D 4
15.4%
A 3
 
11.5%
Z 3
 
11.5%
Q 1
 
3.8%
J 1
 
3.8%
R 1
 
3.8%
X 1
 
3.8%
C 1
 
3.8%
S 1
 
3.8%
Other values (2) 2
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 6
20.0%
3 5
16.7%
0 5
16.7%
1 4
13.3%
9 3
10.0%
8 3
10.0%
4 2
 
6.7%
7 1
 
3.3%
6 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 30
53.6%
Latin 26
46.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 8
30.8%
D 4
15.4%
A 3
 
11.5%
Z 3
 
11.5%
Q 1
 
3.8%
J 1
 
3.8%
R 1
 
3.8%
X 1
 
3.8%
C 1
 
3.8%
S 1
 
3.8%
Other values (2) 2
 
7.7%
Common
ValueCountFrequency (%)
2 6
20.0%
3 5
16.7%
0 5
16.7%
1 4
13.3%
9 3
10.0%
8 3
10.0%
4 2
 
6.7%
7 1
 
3.3%
6 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 8
14.3%
2 6
10.7%
3 5
8.9%
0 5
8.9%
D 4
 
7.1%
1 4
 
7.1%
A 3
 
5.4%
Z 3
 
5.4%
9 3
 
5.4%
8 3
 
5.4%
Other values (11) 12
21.4%

name_prog4
Text

MISSING 

Distinct9
Distinct (%)90.0%
Missing464
Missing (%)97.9%
Memory size15.6 KiB
2023-12-09T22:47:28.114861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length53
Mean length43.9
Min length13

Characters and Unicode

Total characters439
Distinct characters52
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)80.0%

Sample

1st rowZoned Program
2nd rowACATS (The Academy of Computer & Technology Science)
3rd rowZoned Program
4th rowSeth Low (I.S. 96) Magnet Program (Science)
5th rowThe Bay Academy (I.S. 98) Magnet Program (Dance)
ValueCountFrequency (%)
program 8
 
12.1%
i.s 7
 
10.6%
magnet 5
 
7.6%
zoned 3
 
4.5%
the 3
 
4.5%
dance 3
 
4.5%
science 2
 
3.0%
academy 2
 
3.0%
98 1
 
1.5%
bay 1
 
1.5%
Other values (31) 31
47.0%
2023-12-09T22:47:28.479888image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
 
12.8%
e 34
 
7.7%
a 32
 
7.3%
r 29
 
6.6%
o 23
 
5.2%
n 21
 
4.8%
. 17
 
3.9%
g 16
 
3.6%
( 14
 
3.2%
) 14
 
3.2%
Other values (42) 183
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 249
56.7%
Uppercase Letter 69
 
15.7%
Space Separator 56
 
12.8%
Other Punctuation 19
 
4.3%
Decimal Number 18
 
4.1%
Open Punctuation 14
 
3.2%
Close Punctuation 14
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 34
13.7%
a 32
12.9%
r 29
11.6%
o 23
9.2%
n 21
8.4%
g 16
 
6.4%
m 14
 
5.6%
i 13
 
5.2%
t 12
 
4.8%
c 11
 
4.4%
Other values (12) 44
17.7%
Uppercase Letter
ValueCountFrequency (%)
S 14
20.3%
P 8
11.6%
I 8
11.6%
T 6
8.7%
M 6
8.7%
D 5
 
7.2%
A 5
 
7.2%
C 4
 
5.8%
B 3
 
4.3%
Z 3
 
4.3%
Other values (6) 7
10.1%
Decimal Number
ValueCountFrequency (%)
3 4
22.2%
2 4
22.2%
8 3
16.7%
9 3
16.7%
1 1
 
5.6%
6 1
 
5.6%
7 1
 
5.6%
0 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 17
89.5%
/ 1
 
5.3%
& 1
 
5.3%
Space Separator
ValueCountFrequency (%)
56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 318
72.4%
Common 121
 
27.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 34
 
10.7%
a 32
 
10.1%
r 29
 
9.1%
o 23
 
7.2%
n 21
 
6.6%
g 16
 
5.0%
m 14
 
4.4%
S 14
 
4.4%
i 13
 
4.1%
t 12
 
3.8%
Other values (28) 110
34.6%
Common
ValueCountFrequency (%)
56
46.3%
. 17
 
14.0%
( 14
 
11.6%
) 14
 
11.6%
3 4
 
3.3%
2 4
 
3.3%
8 3
 
2.5%
9 3
 
2.5%
1 1
 
0.8%
/ 1
 
0.8%
Other values (4) 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
 
12.8%
e 34
 
7.7%
a 32
 
7.3%
r 29
 
6.6%
o 23
 
5.2%
n 21
 
4.8%
. 17
 
3.9%
g 16
 
3.6%
( 14
 
3.2%
) 14
 
3.2%
Other values (42) 183
41.7%

admissionsmethod_prog4
Text

MISSING 

Distinct3
Distinct (%)30.0%
Missing464
Missing (%)97.9%
Memory size15.3 KiB
2023-12-09T22:47:28.643284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length8.9
Min length5

Characters and Unicode

Total characters89
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)10.0%

Sample

1st rowZoned
2nd rowScreened
3rd rowZoned
4th rowTalent Test
5th rowTalent Test
ValueCountFrequency (%)
talent 6
37.5%
test 6
37.5%
zoned 3
18.8%
screened 1
 
6.2%
2023-12-09T22:47:28.923060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 18
20.2%
T 12
13.5%
t 12
13.5%
n 10
11.2%
a 6
 
6.7%
l 6
 
6.7%
6
 
6.7%
s 6
 
6.7%
d 4
 
4.5%
Z 3
 
3.4%
Other values (4) 6
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 67
75.3%
Uppercase Letter 16
 
18.0%
Space Separator 6
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18
26.9%
t 12
17.9%
n 10
14.9%
a 6
 
9.0%
l 6
 
9.0%
s 6
 
9.0%
d 4
 
6.0%
o 3
 
4.5%
c 1
 
1.5%
r 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
T 12
75.0%
Z 3
 
18.8%
S 1
 
6.2%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 83
93.3%
Common 6
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 18
21.7%
T 12
14.5%
t 12
14.5%
n 10
12.0%
a 6
 
7.2%
l 6
 
7.2%
s 6
 
7.2%
d 4
 
4.8%
Z 3
 
3.6%
o 3
 
3.6%
Other values (3) 3
 
3.6%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 18
20.2%
T 12
13.5%
t 12
13.5%
n 10
11.2%
a 6
 
6.7%
l 6
 
6.7%
6
 
6.7%
s 6
 
6.7%
d 4
 
4.5%
Z 3
 
3.4%
Other values (4) 6
 
6.7%

geapps_prog4
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:29.118219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7
Min length2

Characters and Unicode

Total characters27
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row58
2nd row121
3rd row356
4th row94
5th row163
ValueCountFrequency (%)
139 1
10.0%
141 1
10.0%
326 1
10.0%
27 1
10.0%
356 1
10.0%
121 1
10.0%
462 1
10.0%
163 1
10.0%
58 1
10.0%
94 1
10.0%
2023-12-09T22:47:29.429465image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
22.2%
3 4
14.8%
2 4
14.8%
6 4
14.8%
4 3
11.1%
9 2
 
7.4%
5 2
 
7.4%
7 1
 
3.7%
8 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
22.2%
3 4
14.8%
2 4
14.8%
6 4
14.8%
4 3
11.1%
9 2
 
7.4%
5 2
 
7.4%
7 1
 
3.7%
8 1
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 27
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
22.2%
3 4
14.8%
2 4
14.8%
6 4
14.8%
4 3
11.1%
9 2
 
7.4%
5 2
 
7.4%
7 1
 
3.7%
8 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
22.2%
3 4
14.8%
2 4
14.8%
6 4
14.8%
4 3
11.1%
9 2
 
7.4%
5 2
 
7.4%
7 1
 
3.7%
8 1
 
3.7%

swdapps_prog4
Text

MISSING 

Distinct9
Distinct (%)90.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:29.593334image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.9
Min length1

Characters and Unicode

Total characters19
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)80.0%

Sample

1st row17
2nd row47
3rd row62
4th row12
5th row19
ValueCountFrequency (%)
12 2
20.0%
29 1
10.0%
19 1
10.0%
62 1
10.0%
7 1
10.0%
57 1
10.0%
21 1
10.0%
47 1
10.0%
17 1
10.0%
2023-12-09T22:47:29.864740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
26.3%
2 5
26.3%
7 4
21.1%
9 2
 
10.5%
6 1
 
5.3%
5 1
 
5.3%
4 1
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
26.3%
2 5
26.3%
7 4
21.1%
9 2
 
10.5%
6 1
 
5.3%
5 1
 
5.3%
4 1
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 19
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
26.3%
2 5
26.3%
7 4
21.1%
9 2
 
10.5%
6 1
 
5.3%
5 1
 
5.3%
4 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
26.3%
2 5
26.3%
7 4
21.1%
9 2
 
10.5%
6 1
 
5.3%
5 1
 
5.3%
4 1
 
5.3%

geappsperseat_prog4
Text

MISSING 

Distinct6
Distinct (%)60.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:29.993099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters12
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)40.0%

Sample

1st row1
2nd row5
3rd row1
4th row4
5th row5
ValueCountFrequency (%)
1 4
40.0%
5 2
20.0%
7 1
 
10.0%
20 1
 
10.0%
4 1
 
10.0%
14 1
 
10.0%
2023-12-09T22:47:30.661115image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
41.7%
5 2
 
16.7%
4 2
 
16.7%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
41.7%
5 2
 
16.7%
4 2
 
16.7%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
41.7%
5 2
 
16.7%
4 2
 
16.7%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
41.7%
5 2
 
16.7%
4 2
 
16.7%
7 1
 
8.3%
2 1
 
8.3%
0 1
 
8.3%

swdappsperseat_prog4
Text

MISSING 

Distinct6
Distinct (%)60.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:30.775492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.1
Min length1

Characters and Unicode

Total characters11
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)40.0%

Sample

1st row1
2nd row8
3rd row1
4th row3
5th row3
ValueCountFrequency (%)
1 4
40.0%
3 2
20.0%
11 1
 
10.0%
6 1
 
10.0%
8 1
 
10.0%
2 1
 
10.0%
2023-12-09T22:47:30.999955image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
54.5%
3 2
 
18.2%
6 1
 
9.1%
8 1
 
9.1%
2 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
54.5%
3 2
 
18.2%
6 1
 
9.1%
8 1
 
9.1%
2 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
54.5%
3 2
 
18.2%
6 1
 
9.1%
8 1
 
9.1%
2 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
54.5%
3 2
 
18.2%
6 1
 
9.1%
8 1
 
9.1%
2 1
 
9.1%

swdseats_prog4
Text

MISSING 

Distinct8
Distinct (%)80.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:31.128855image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.3
Min length1

Characters and Unicode

Total characters13
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)70.0%

Sample

1st row13
2nd row6
3rd row69
4th row4
5th row7
ValueCountFrequency (%)
5 3
30.0%
69 1
 
10.0%
7 1
 
10.0%
6 1
 
10.0%
64 1
 
10.0%
13 1
 
10.0%
4 1
 
10.0%
2 1
 
10.0%
2023-12-09T22:47:31.377998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3
23.1%
6 3
23.1%
4 2
15.4%
9 1
 
7.7%
7 1
 
7.7%
1 1
 
7.7%
3 1
 
7.7%
2 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3
23.1%
6 3
23.1%
4 2
15.4%
9 1
 
7.7%
7 1
 
7.7%
1 1
 
7.7%
3 1
 
7.7%
2 1
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Common 13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3
23.1%
6 3
23.1%
4 2
15.4%
9 1
 
7.7%
7 1
 
7.7%
1 1
 
7.7%
3 1
 
7.7%
2 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3
23.1%
6 3
23.1%
4 2
15.4%
9 1
 
7.7%
7 1
 
7.7%
1 1
 
7.7%
3 1
 
7.7%
2 1
 
7.7%

geseats_prog4
Text

MISSING 

Distinct8
Distinct (%)80.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:31.555409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2
Min length2

Characters and Unicode

Total characters22
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)60.0%

Sample

1st row57
2nd row24
3rd row341
4th row24
5th row30
ValueCountFrequency (%)
23 2
20.0%
24 2
20.0%
30 1
10.0%
341 1
10.0%
57 1
10.0%
20 1
10.0%
10 1
10.0%
272 1
10.0%
2023-12-09T22:47:31.844881image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7
31.8%
3 4
18.2%
4 3
13.6%
0 3
13.6%
1 2
 
9.1%
7 2
 
9.1%
5 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 7
31.8%
3 4
18.2%
4 3
13.6%
0 3
13.6%
1 2
 
9.1%
7 2
 
9.1%
5 1
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 7
31.8%
3 4
18.2%
4 3
13.6%
0 3
13.6%
1 2
 
9.1%
7 2
 
9.1%
5 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 7
31.8%
3 4
18.2%
4 3
13.6%
0 3
13.6%
1 2
 
9.1%
7 2
 
9.1%
5 1
 
4.5%

gefilled_prog4
Text

MISSING 

Distinct2
Distinct (%)20.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:31.951148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters10
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowN
5th rowY
ValueCountFrequency (%)
n 6
60.0%
y 4
40.0%
2023-12-09T22:47:32.159032image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 6
60.0%
Y 4
40.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 6
60.0%
Y 4
40.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 6
60.0%
Y 4
40.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 6
60.0%
Y 4
40.0%

swdfilled_prog4
Text

MISSING 

Distinct2
Distinct (%)20.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:47:32.263011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters10
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 7
70.0%
y 3
30.0%
2023-12-09T22:47:32.472297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 7
70.0%
Y 3
30.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 7
70.0%
Y 3
30.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 7
70.0%
Y 3
30.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 7
70.0%
Y 3
30.0%

eligibility_prog4
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing464
Missing (%)97.9%
Memory size15.6 KiB
2023-12-09T22:47:32.657427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length41.3
Min length31

Characters and Unicode

Total characters413
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)30.0%

Sample

1st rowOpen to students residing in the zone.
2nd rowOpen to students and residents of District 13
3rd rowOpen to students residing in the zone
4th rowOpen to students and residents of District 21
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 10
13.3%
to 10
13.3%
students 9
12.0%
residents 7
9.3%
and 6
8.0%
of 6
8.0%
district 6
8.0%
21 5
6.7%
residing 3
 
4.0%
in 3
 
4.0%
Other values (6) 10
13.3%
2023-12-09T22:47:32.972803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
15.7%
t 51
12.3%
e 43
10.4%
n 41
9.9%
s 41
9.9%
i 29
7.0%
d 25
 
6.1%
o 20
 
4.8%
r 17
 
4.1%
O 10
 
2.4%
Other values (19) 71
17.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 316
76.5%
Space Separator 65
 
15.7%
Uppercase Letter 19
 
4.6%
Decimal Number 12
 
2.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 51
16.1%
e 43
13.6%
n 41
13.0%
s 41
13.0%
i 29
9.2%
d 25
7.9%
o 20
 
6.3%
r 17
 
5.4%
p 10
 
3.2%
u 9
 
2.8%
Other values (9) 30
9.5%
Uppercase Letter
ValueCountFrequency (%)
O 10
52.6%
D 6
31.6%
N 1
 
5.3%
Y 1
 
5.3%
C 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
2 5
41.7%
3 1
 
8.3%
Space Separator
ValueCountFrequency (%)
65
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 335
81.1%
Common 78
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 51
15.2%
e 43
12.8%
n 41
12.2%
s 41
12.2%
i 29
8.7%
d 25
7.5%
o 20
 
6.0%
r 17
 
5.1%
O 10
 
3.0%
p 10
 
3.0%
Other values (14) 48
14.3%
Common
ValueCountFrequency (%)
65
83.3%
1 6
 
7.7%
2 5
 
6.4%
. 1
 
1.3%
3 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
15.7%
t 51
12.3%
e 43
10.4%
n 41
9.9%
s 41
9.9%
i 29
7.0%
d 25
 
6.1%
o 20
 
4.8%
r 17
 
4.1%
O 10
 
2.4%
Other values (19) 71
17.2%

priority1_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog5
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:33.153472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.833333333
Min length5

Characters and Unicode

Total characters35
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowK096ST
2nd rowK098DR
3rd rowK228DR
4th rowK239DR
5th rowK281M
ValueCountFrequency (%)
k303jo 1
16.7%
k239dr 1
16.7%
k098dr 1
16.7%
k228dr 1
16.7%
k096st 1
16.7%
k281m 1
16.7%
2023-12-09T22:47:33.452792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 6
17.1%
2 4
11.4%
3 3
8.6%
0 3
8.6%
9 3
8.6%
D 3
8.6%
R 3
8.6%
8 3
8.6%
J 1
 
2.9%
O 1
 
2.9%
Other values (5) 5
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
51.4%
Uppercase Letter 17
48.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 6
35.3%
D 3
17.6%
R 3
17.6%
J 1
 
5.9%
O 1
 
5.9%
S 1
 
5.9%
T 1
 
5.9%
M 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 4
22.2%
3 3
16.7%
0 3
16.7%
9 3
16.7%
8 3
16.7%
6 1
 
5.6%
1 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 18
51.4%
Latin 17
48.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 6
35.3%
D 3
17.6%
R 3
17.6%
J 1
 
5.9%
O 1
 
5.9%
S 1
 
5.9%
T 1
 
5.9%
M 1
 
5.9%
Common
ValueCountFrequency (%)
2 4
22.2%
3 3
16.7%
0 3
16.7%
9 3
16.7%
8 3
16.7%
6 1
 
5.6%
1 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 6
17.1%
2 4
11.4%
3 3
8.6%
0 3
8.6%
9 3
8.6%
D 3
8.6%
R 3
8.6%
8 3
8.6%
J 1
 
2.9%
O 1
 
2.9%
Other values (5) 5
14.3%

name_prog5
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.4 KiB
2023-12-09T22:47:33.681406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length76
Median length58.5
Mean length53
Min length29

Characters and Unicode

Total characters318
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSeth Low (I.S. 96) Magnet Program (Instrumental-Strings)
2nd rowThe Bay Academy (I.S. 98) Magnet Program (Drama)
3rd rowDavid A. Boody (I.S. 228) Magnet Program (Drama)
4th rowMark Twain (I.S. 239) (Drama)
5th rowJoseph B. Cavallaro (I.S. 281) Mandarin Dual Language Program
ValueCountFrequency (%)
i.s 6
 
13.0%
program 5
 
10.9%
magnet 4
 
8.7%
drama 3
 
6.5%
228 1
 
2.2%
joseph 1
 
2.2%
b 1
 
2.2%
cavallaro 1
 
2.2%
281 1
 
2.2%
mandarin 1
 
2.2%
Other values (22) 22
47.8%
2023-12-09T22:47:34.029900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
 
12.6%
a 31
 
9.7%
r 24
 
7.5%
e 16
 
5.0%
. 15
 
4.7%
g 14
 
4.4%
n 14
 
4.4%
) 11
 
3.5%
t 11
 
3.5%
( 11
 
3.5%
Other values (38) 131
41.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 175
55.0%
Uppercase Letter 48
 
15.1%
Space Separator 40
 
12.6%
Other Punctuation 16
 
5.0%
Decimal Number 16
 
5.0%
Close Punctuation 11
 
3.5%
Open Punctuation 11
 
3.5%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 31
17.7%
r 24
13.7%
e 16
9.1%
g 14
8.0%
n 14
8.0%
t 11
 
6.3%
m 11
 
6.3%
o 11
 
6.3%
i 9
 
5.1%
l 5
 
2.9%
Other values (11) 29
16.6%
Uppercase Letter
ValueCountFrequency (%)
S 9
18.8%
I 7
14.6%
M 6
12.5%
P 5
10.4%
D 5
10.4%
B 3
 
6.2%
J 2
 
4.2%
L 2
 
4.2%
C 2
 
4.2%
T 2
 
4.2%
Other values (4) 5
10.4%
Decimal Number
ValueCountFrequency (%)
2 4
25.0%
9 3
18.8%
3 3
18.8%
8 3
18.8%
1 1
 
6.2%
6 1
 
6.2%
0 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 15
93.8%
/ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 223
70.1%
Common 95
29.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 31
13.9%
r 24
 
10.8%
e 16
 
7.2%
g 14
 
6.3%
n 14
 
6.3%
t 11
 
4.9%
m 11
 
4.9%
o 11
 
4.9%
S 9
 
4.0%
i 9
 
4.0%
Other values (25) 73
32.7%
Common
ValueCountFrequency (%)
40
42.1%
. 15
 
15.8%
) 11
 
11.6%
( 11
 
11.6%
2 4
 
4.2%
9 3
 
3.2%
3 3
 
3.2%
8 3
 
3.2%
1 1
 
1.1%
- 1
 
1.1%
Other values (3) 3
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
 
12.6%
a 31
 
9.7%
r 24
 
7.5%
e 16
 
5.0%
. 15
 
4.7%
g 14
 
4.4%
n 14
 
4.4%
) 11
 
3.5%
t 11
 
3.5%
( 11
 
3.5%
Other values (38) 131
41.2%

admissionsmethod_prog5
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.2 KiB
2023-12-09T22:47:34.196944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length12.16666667
Min length11

Characters and Unicode

Total characters73
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowTalent Test
2nd rowTalent Test
3rd rowTalent Test
4th rowTalent Test
5th rowScreened: Language
ValueCountFrequency (%)
talent 5
41.7%
test 5
41.7%
screened 1
 
8.3%
language 1
 
8.3%
2023-12-09T22:47:34.478761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 14
19.2%
T 10
13.7%
t 10
13.7%
a 7
9.6%
n 7
9.6%
6
8.2%
l 5
 
6.8%
s 5
 
6.8%
g 2
 
2.7%
S 1
 
1.4%
Other values (6) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 54
74.0%
Uppercase Letter 12
 
16.4%
Space Separator 6
 
8.2%
Other Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14
25.9%
t 10
18.5%
a 7
13.0%
n 7
13.0%
l 5
 
9.3%
s 5
 
9.3%
g 2
 
3.7%
c 1
 
1.9%
r 1
 
1.9%
d 1
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
T 10
83.3%
S 1
 
8.3%
L 1
 
8.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 66
90.4%
Common 7
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14
21.2%
T 10
15.2%
t 10
15.2%
a 7
10.6%
n 7
10.6%
l 5
 
7.6%
s 5
 
7.6%
g 2
 
3.0%
S 1
 
1.5%
c 1
 
1.5%
Other values (4) 4
 
6.1%
Common
ValueCountFrequency (%)
6
85.7%
: 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 14
19.2%
T 10
13.7%
t 10
13.7%
a 7
9.6%
n 7
9.6%
6
8.2%
l 5
 
6.8%
s 5
 
6.8%
g 2
 
2.7%
S 1
 
1.4%
Other values (6) 6
8.2%

geapps_prog5
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:34.658154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Characters and Unicode

Total characters15
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row25
2nd row151
3rd row123
4th row457
5th row87
ValueCountFrequency (%)
25 1
16.7%
151 1
16.7%
123 1
16.7%
89 1
16.7%
457 1
16.7%
87 1
16.7%
2023-12-09T22:47:34.953677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3
20.0%
1 3
20.0%
2 2
13.3%
8 2
13.3%
7 2
13.3%
3 1
 
6.7%
9 1
 
6.7%
4 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3
20.0%
1 3
20.0%
2 2
13.3%
8 2
13.3%
7 2
13.3%
3 1
 
6.7%
9 1
 
6.7%
4 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3
20.0%
1 3
20.0%
2 2
13.3%
8 2
13.3%
7 2
13.3%
3 1
 
6.7%
9 1
 
6.7%
4 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3
20.0%
1 3
20.0%
2 2
13.3%
8 2
13.3%
7 2
13.3%
3 1
 
6.7%
9 1
 
6.7%
4 1
 
6.7%

swdapps_prog5
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:35.117947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.666666667
Min length1

Characters and Unicode

Total characters10
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row2
2nd row14
3rd row12
4th row37
5th row13
ValueCountFrequency (%)
12 1
16.7%
37 1
16.7%
14 1
16.7%
13 1
16.7%
4 1
16.7%
2 1
16.7%
2023-12-09T22:47:35.391775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
3 2
20.0%
4 2
20.0%
7 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
3 2
20.0%
4 2
20.0%
7 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
3 2
20.0%
4 2
20.0%
7 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
3 2
20.0%
4 2
20.0%
7 1
 
10.0%

geappsperseat_prog5
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:35.524881image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row3
2nd row5
3rd row15
4th row20
5th row4
ValueCountFrequency (%)
3 2
33.3%
15 1
16.7%
5 1
16.7%
20 1
16.7%
4 1
16.7%
2023-12-09T22:47:35.766197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
25.0%
5 2
25.0%
1 1
12.5%
2 1
12.5%
0 1
12.5%
4 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2
25.0%
5 2
25.0%
1 1
12.5%
2 1
12.5%
0 1
12.5%
4 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2
25.0%
5 2
25.0%
1 1
12.5%
2 1
12.5%
0 1
12.5%
4 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
25.0%
5 2
25.0%
1 1
12.5%
2 1
12.5%
0 1
12.5%
4 1
12.5%

swdappsperseat_prog5
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:35.880845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row1
2nd row2
3rd row6
4th row7
5th row3
ValueCountFrequency (%)
1 2
33.3%
3 1
16.7%
7 1
16.7%
6 1
16.7%
2 1
16.7%
2023-12-09T22:47:36.105095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
33.3%
3 1
16.7%
7 1
16.7%
6 1
16.7%
2 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
33.3%
3 1
16.7%
7 1
16.7%
6 1
16.7%
2 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
33.3%
3 1
16.7%
7 1
16.7%
6 1
16.7%
2 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
33.3%
3 1
16.7%
7 1
16.7%
6 1
16.7%
2 1
16.7%

swdseats_prog5
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:36.224993image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row2
2nd row7
3rd row2
4th row5
5th row5
ValueCountFrequency (%)
5 2
33.3%
2 2
33.3%
7 1
16.7%
6 1
16.7%
2023-12-09T22:47:36.457194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
33.3%
2 2
33.3%
7 1
16.7%
6 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
33.3%
2 2
33.3%
7 1
16.7%
6 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
33.3%
2 2
33.3%
7 1
16.7%
6 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
33.3%
2 2
33.3%
7 1
16.7%
6 1
16.7%

geseats_prog5
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:36.595968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.666666667
Min length1

Characters and Unicode

Total characters10
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row8
2nd row29
3rd row8
4th row23
5th row20
ValueCountFrequency (%)
8 2
33.3%
29 1
16.7%
23 1
16.7%
27 1
16.7%
20 1
16.7%
2023-12-09T22:47:36.842022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
40.0%
8 2
20.0%
9 1
 
10.0%
3 1
 
10.0%
7 1
 
10.0%
0 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
40.0%
8 2
20.0%
9 1
 
10.0%
3 1
 
10.0%
7 1
 
10.0%
0 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
40.0%
8 2
20.0%
9 1
 
10.0%
3 1
 
10.0%
7 1
 
10.0%
0 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
40.0%
8 2
20.0%
9 1
 
10.0%
3 1
 
10.0%
7 1
 
10.0%
0 1
 
10.0%

gefilled_prog5
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:36.948729image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 4
66.7%
n 2
33.3%
2023-12-09T22:47:37.164378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

swdfilled_prog5
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:37.268097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowY
5th rowN
ValueCountFrequency (%)
n 5
83.3%
y 1
 
16.7%
2023-12-09T22:47:37.482825image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

eligibility_prog5
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.3 KiB
2023-12-09T22:47:37.664043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length42.16666667
Min length31

Characters and Unicode

Total characters253
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of District 21
3rd rowOpen to students and residents of District 21
4th rowOpen to New York City residents
5th rowOpen to students and residents of Brooklyn
ValueCountFrequency (%)
open 6
13.3%
to 6
13.3%
residents 6
13.3%
students 5
11.1%
and 5
11.1%
of 5
11.1%
district 4
8.9%
21 4
8.9%
brooklyn 1
 
2.2%
new 1
 
2.2%
Other values (2) 2
 
4.4%
2023-12-09T22:47:37.967235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 192
75.9%
Space Separator 39
 
15.4%
Uppercase Letter 14
 
5.5%
Decimal Number 8
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 31
16.1%
s 26
13.5%
e 24
12.5%
n 23
12.0%
d 16
8.3%
i 15
7.8%
o 14
7.3%
r 12
 
6.2%
p 6
 
3.1%
f 5
 
2.6%
Other values (7) 20
10.4%
Uppercase Letter
ValueCountFrequency (%)
O 6
42.9%
D 4
28.6%
B 1
 
7.1%
N 1
 
7.1%
Y 1
 
7.1%
C 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 206
81.4%
Common 47
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 31
15.0%
s 26
12.6%
e 24
11.7%
n 23
11.2%
d 16
7.8%
i 15
7.3%
o 14
6.8%
r 12
 
5.8%
O 6
 
2.9%
p 6
 
2.9%
Other values (13) 33
16.0%
Common
ValueCountFrequency (%)
39
83.0%
2 4
 
8.5%
1 4
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

priority1_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:38.156014image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.833333333
Min length5

Characters and Unicode

Total characters35
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowK096U
2nd rowK098JO
3rd rowK228JO
4th rowK239JO
5th rowK281SC
ValueCountFrequency (%)
k096u 1
16.7%
k228jo 1
16.7%
k098jo 1
16.7%
k239jo 1
16.7%
k281sc 1
16.7%
k303me 1
16.7%
2023-12-09T22:47:38.467884image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 6
17.1%
2 4
11.4%
0 3
8.6%
9 3
8.6%
8 3
8.6%
J 3
8.6%
O 3
8.6%
3 3
8.6%
6 1
 
2.9%
U 1
 
2.9%
Other values (5) 5
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
51.4%
Uppercase Letter 17
48.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 6
35.3%
J 3
17.6%
O 3
17.6%
U 1
 
5.9%
S 1
 
5.9%
C 1
 
5.9%
M 1
 
5.9%
E 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 4
22.2%
0 3
16.7%
9 3
16.7%
8 3
16.7%
3 3
16.7%
6 1
 
5.6%
1 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 18
51.4%
Latin 17
48.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 6
35.3%
J 3
17.6%
O 3
17.6%
U 1
 
5.9%
S 1
 
5.9%
C 1
 
5.9%
M 1
 
5.9%
E 1
 
5.9%
Common
ValueCountFrequency (%)
2 4
22.2%
0 3
16.7%
9 3
16.7%
8 3
16.7%
3 3
16.7%
6 1
 
5.6%
1 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 6
17.1%
2 4
11.4%
0 3
8.6%
9 3
8.6%
8 3
8.6%
J 3
8.6%
O 3
8.6%
3 3
8.6%
6 1
 
2.9%
U 1
 
2.9%
Other values (5) 5
14.3%

name_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.4 KiB
2023-12-09T22:47:38.691088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length70
Median length54.5
Mean length53
Min length18

Characters and Unicode

Total characters318
Distinct characters47
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSeth Low (I.S. 96)
2nd rowThe Bay Academy (I.S. 98) Magnet Program (Creative Writing/Journalism)
3rd rowDavid A. Boody (I.S. 228) Magnet Program (Creative Writing/Journalism)
4th rowMark Twain (I.S. 239) (Creative Writing/Journalism)
5th rowJoseph B. Cavallaro (I.S. 281) Magnet Program (Science)
ValueCountFrequency (%)
i.s 6
 
13.6%
magnet 4
 
9.1%
program 4
 
9.1%
writing/journalism 3
 
6.8%
creative 3
 
6.8%
science 1
 
2.3%
joseph 1
 
2.3%
b 1
 
2.3%
cavallaro 1
 
2.3%
281 1
 
2.3%
Other values (19) 19
43.2%
2023-12-09T22:47:39.027200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
11.9%
a 23
 
7.2%
r 22
 
6.9%
e 21
 
6.6%
i 17
 
5.3%
. 15
 
4.7%
n 13
 
4.1%
t 12
 
3.8%
g 12
 
3.8%
o 12
 
3.8%
Other values (37) 133
41.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 177
55.7%
Uppercase Letter 47
 
14.8%
Space Separator 38
 
11.9%
Other Punctuation 18
 
5.7%
Decimal Number 16
 
5.0%
Close Punctuation 11
 
3.5%
Open Punctuation 11
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 23
13.0%
r 22
12.4%
e 21
11.9%
i 17
9.6%
n 13
7.3%
t 12
 
6.8%
g 12
 
6.8%
o 12
 
6.8%
m 8
 
4.5%
l 5
 
2.8%
Other values (11) 32
18.1%
Uppercase Letter
ValueCountFrequency (%)
S 9
19.1%
I 6
12.8%
M 6
12.8%
C 4
8.5%
J 4
8.5%
P 4
8.5%
W 3
 
6.4%
B 3
 
6.4%
T 2
 
4.3%
A 2
 
4.3%
Other values (4) 4
8.5%
Decimal Number
ValueCountFrequency (%)
2 4
25.0%
3 3
18.8%
8 3
18.8%
9 3
18.8%
1 1
 
6.2%
6 1
 
6.2%
0 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 15
83.3%
/ 3
 
16.7%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 224
70.4%
Common 94
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 23
 
10.3%
r 22
 
9.8%
e 21
 
9.4%
i 17
 
7.6%
n 13
 
5.8%
t 12
 
5.4%
g 12
 
5.4%
o 12
 
5.4%
S 9
 
4.0%
m 8
 
3.6%
Other values (25) 75
33.5%
Common
ValueCountFrequency (%)
38
40.4%
. 15
 
16.0%
) 11
 
11.7%
( 11
 
11.7%
2 4
 
4.3%
3 3
 
3.2%
/ 3
 
3.2%
8 3
 
3.2%
9 3
 
3.2%
1 1
 
1.1%
Other values (2) 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
 
11.9%
a 23
 
7.2%
r 22
 
6.9%
e 21
 
6.6%
i 17
 
5.3%
. 15
 
4.7%
n 13
 
4.1%
t 12
 
3.8%
g 12
 
3.8%
o 12
 
3.8%
Other values (37) 133
41.8%

admissionsmethod_prog6
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:39.182867image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length9.833333333
Min length4

Characters and Unicode

Total characters59
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowOpen
2nd rowTalent Test
3rd rowTalent Test
4th rowTalent Test
5th rowTalent Test
ValueCountFrequency (%)
talent 5
45.5%
test 5
45.5%
open 1
 
9.1%
2023-12-09T22:47:39.448601image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11
18.6%
T 10
16.9%
t 10
16.9%
n 6
10.2%
a 5
8.5%
l 5
8.5%
5
8.5%
s 5
8.5%
O 1
 
1.7%
p 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43
72.9%
Uppercase Letter 11
 
18.6%
Space Separator 5
 
8.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
25.6%
t 10
23.3%
n 6
14.0%
a 5
11.6%
l 5
11.6%
s 5
11.6%
p 1
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
T 10
90.9%
O 1
 
9.1%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 54
91.5%
Common 5
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
20.4%
T 10
18.5%
t 10
18.5%
n 6
11.1%
a 5
9.3%
l 5
9.3%
s 5
9.3%
O 1
 
1.9%
p 1
 
1.9%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 11
18.6%
T 10
16.9%
t 10
16.9%
n 6
10.2%
a 5
8.5%
l 5
8.5%
5
8.5%
s 5
8.5%
O 1
 
1.7%
p 1
 
1.7%

geapps_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:39.623230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.666666667
Min length1

Characters and Unicode

Total characters16
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row475
2nd row371
3rd row243
4th row848
5th row220
ValueCountFrequency (%)
848 1
16.7%
371 1
16.7%
475 1
16.7%
9 1
16.7%
220 1
16.7%
243 1
16.7%
2023-12-09T22:47:39.923462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 3
18.8%
2 3
18.8%
8 2
12.5%
3 2
12.5%
7 2
12.5%
1 1
 
6.2%
5 1
 
6.2%
9 1
 
6.2%
0 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 3
18.8%
2 3
18.8%
8 2
12.5%
3 2
12.5%
7 2
12.5%
1 1
 
6.2%
5 1
 
6.2%
9 1
 
6.2%
0 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 16
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 3
18.8%
2 3
18.8%
8 2
12.5%
3 2
12.5%
7 2
12.5%
1 1
 
6.2%
5 1
 
6.2%
9 1
 
6.2%
0 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 3
18.8%
2 3
18.8%
8 2
12.5%
3 2
12.5%
7 2
12.5%
1 1
 
6.2%
5 1
 
6.2%
9 1
 
6.2%
0 1
 
6.2%

swdapps_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:40.149444image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters12
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row104
2nd row20
3rd row18
4th row28
5th row25
ValueCountFrequency (%)
25 1
16.7%
18 1
16.7%
5 1
16.7%
20 1
16.7%
28 1
16.7%
104 1
16.7%
2023-12-09T22:47:40.612844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
1 2
16.7%
8 2
16.7%
0 2
16.7%
4 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
1 2
16.7%
8 2
16.7%
0 2
16.7%
4 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
1 2
16.7%
8 2
16.7%
0 2
16.7%
4 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
1 2
16.7%
8 2
16.7%
0 2
16.7%
4 1
 
8.3%

geappsperseat_prog6
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:40.750316image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1.5
Mean length1.5
Min length1

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row4
2nd row4
3rd row41
4th row18
5th row11
ValueCountFrequency (%)
4 2
33.3%
11 1
16.7%
0 1
16.7%
41 1
16.7%
18 1
16.7%
2023-12-09T22:47:41.002728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
44.4%
4 3
33.3%
0 1
 
11.1%
8 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
44.4%
4 3
33.3%
0 1
 
11.1%
8 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
44.4%
4 3
33.3%
0 1
 
11.1%
8 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
44.4%
4 3
33.3%
0 1
 
11.1%
8 1
 
11.1%

swdappsperseat_prog6
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:41.125677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.166666667
Min length1

Characters and Unicode

Total characters7
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row3
2nd row1
3rd row18
4th row2
5th row5
ValueCountFrequency (%)
1 2
33.3%
3 1
16.7%
18 1
16.7%
5 1
16.7%
2 1
16.7%
2023-12-09T22:47:41.362354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
42.9%
3 1
 
14.3%
8 1
 
14.3%
5 1
 
14.3%
2 1
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
42.9%
3 1
 
14.3%
8 1
 
14.3%
5 1
 
14.3%
2 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
42.9%
3 1
 
14.3%
8 1
 
14.3%
5 1
 
14.3%
2 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
42.9%
3 1
 
14.3%
8 1
 
14.3%
5 1
 
14.3%
2 1
 
14.3%

swdseats_prog6
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:41.497637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1.5
Mean length1.5
Min length1

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row32
2nd row21
3rd row1
4th row12
5th row5
ValueCountFrequency (%)
5 2
33.3%
12 1
16.7%
32 1
16.7%
1 1
16.7%
21 1
16.7%
2023-12-09T22:47:41.751949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
33.3%
2 3
33.3%
5 2
22.2%
3 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
33.3%
2 3
33.3%
5 2
22.2%
3 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
33.3%
2 3
33.3%
5 2
22.2%
3 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
33.3%
2 3
33.3%
5 2
22.2%
3 1
 
11.1%

geseats_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:41.927760image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters12
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row133
2nd row86
3rd row6
4th row48
5th row20
ValueCountFrequency (%)
20 1
16.7%
133 1
16.7%
6 1
16.7%
48 1
16.7%
86 1
16.7%
23 1
16.7%
2023-12-09T22:47:42.227098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3
25.0%
2 2
16.7%
6 2
16.7%
8 2
16.7%
0 1
 
8.3%
1 1
 
8.3%
4 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3
25.0%
2 2
16.7%
6 2
16.7%
8 2
16.7%
0 1
 
8.3%
1 1
 
8.3%
4 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 3
25.0%
2 2
16.7%
6 2
16.7%
8 2
16.7%
0 1
 
8.3%
1 1
 
8.3%
4 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 3
25.0%
2 2
16.7%
6 2
16.7%
8 2
16.7%
0 1
 
8.3%
1 1
 
8.3%
4 1
 
8.3%

gefilled_prog6
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:42.335282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 5
83.3%
n 1
 
16.7%
2023-12-09T22:47:42.546346image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 5
83.3%
N 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 5
83.3%
N 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 5
83.3%
N 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 5
83.3%
N 1
 
16.7%

swdfilled_prog6
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:42.648766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowY
2nd rowN
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 5
83.3%
y 1
 
16.7%
2023-12-09T22:47:43.418315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 5
83.3%
Y 1
 
16.7%

eligibility_prog6
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.3 KiB
2023-12-09T22:47:43.599072image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length42.66666667
Min length31

Characters and Unicode

Total characters256
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of District 21
3rd rowOpen to students and residents of District 21
4th rowOpen to New York City residents
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 6
13.0%
to 6
13.0%
residents 6
13.0%
students 5
10.9%
and 5
10.9%
of 5
10.9%
district 5
10.9%
21 5
10.9%
new 1
 
2.2%
york 1
 
2.2%
2023-12-09T22:47:43.901055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
15.6%
t 33
12.9%
s 27
10.5%
e 24
9.4%
n 22
8.6%
i 17
 
6.6%
d 16
 
6.2%
r 12
 
4.7%
o 12
 
4.7%
p 6
 
2.3%
Other values (14) 47
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 192
75.0%
Space Separator 40
 
15.6%
Uppercase Letter 14
 
5.5%
Decimal Number 10
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 33
17.2%
s 27
14.1%
e 24
12.5%
n 22
11.5%
i 17
8.9%
d 16
8.3%
r 12
 
6.2%
o 12
 
6.2%
p 6
 
3.1%
a 5
 
2.6%
Other values (6) 18
9.4%
Uppercase Letter
ValueCountFrequency (%)
O 6
42.9%
D 5
35.7%
N 1
 
7.1%
Y 1
 
7.1%
C 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 5
50.0%
1 5
50.0%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 206
80.5%
Common 50
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 33
16.0%
s 27
13.1%
e 24
11.7%
n 22
10.7%
i 17
8.3%
d 16
7.8%
r 12
 
5.8%
o 12
 
5.8%
p 6
 
2.9%
O 6
 
2.9%
Other values (11) 31
15.0%
Common
ValueCountFrequency (%)
40
80.0%
2 5
 
10.0%
1 5
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
15.6%
t 33
12.9%
s 27
10.5%
e 24
9.4%
n 22
8.6%
i 17
 
6.6%
d 16
 
6.2%
r 12
 
4.7%
o 12
 
4.7%
p 6
 
2.3%
Other values (14) 47
18.4%

priority1_prog6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:47:44.082334image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPriority to residents of the middle school zone
ValueCountFrequency (%)
priority 1
12.5%
to 1
12.5%
residents 1
12.5%
of 1
12.5%
the 1
12.5%
middle 1
12.5%
school 1
12.5%
zone 1
12.5%
2023-12-09T22:47:44.372917image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
83.0%
Space Separator 7
 
14.9%
Uppercase Letter 1
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
15.4%
e 5
12.8%
i 4
10.3%
t 4
10.3%
s 3
7.7%
r 3
7.7%
d 3
7.7%
n 2
 
5.1%
l 2
 
5.1%
h 2
 
5.1%
Other values (5) 5
12.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
85.1%
Common 7
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
e 5
12.5%
i 4
10.0%
t 4
10.0%
s 3
7.5%
r 3
7.5%
d 3
7.5%
n 2
 
5.0%
l 2
 
5.0%
h 2
 
5.0%
Other values (6) 6
15.0%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

priority2_prog6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:47:44.562012image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to District 21 students and residents
ValueCountFrequency (%)
then 1
14.3%
to 1
14.3%
district 1
14.3%
21 1
14.3%
students 1
14.3%
and 1
14.3%
residents 1
14.3%
2023-12-09T22:47:44.851735image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
76.2%
Space Separator 6
 
14.3%
Decimal Number 2
 
4.8%
Uppercase Letter 2
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
18.8%
s 5
15.6%
e 4
12.5%
n 4
12.5%
i 3
9.4%
d 3
9.4%
r 2
 
6.2%
u 1
 
3.1%
c 1
 
3.1%
h 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
81.0%
Common 8
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
i 3
8.8%
d 3
8.8%
r 2
 
5.9%
u 1
 
2.9%
T 1
 
2.9%
c 1
 
2.9%
Other values (4) 4
11.8%
Common
ValueCountFrequency (%)
6
75.0%
2 1
 
12.5%
1 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

priority3_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:45.038406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.666666667
Min length5

Characters and Unicode

Total characters34
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowK096WI
2nd rowK098SC
3rd rowK228M
4th rowK239ME
5th rowK281U
ValueCountFrequency (%)
k096wi 1
16.7%
k303sc 1
16.7%
k239me 1
16.7%
k281u 1
16.7%
k098sc 1
16.7%
k228m 1
16.7%
2023-12-09T22:47:45.336957image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 6
17.6%
2 4
11.8%
0 3
8.8%
9 3
8.8%
3 3
8.8%
8 3
8.8%
S 2
 
5.9%
C 2
 
5.9%
M 2
 
5.9%
6 1
 
2.9%
Other values (5) 5
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
52.9%
Uppercase Letter 16
47.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 6
37.5%
S 2
 
12.5%
C 2
 
12.5%
M 2
 
12.5%
W 1
 
6.2%
I 1
 
6.2%
E 1
 
6.2%
U 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 4
22.2%
0 3
16.7%
9 3
16.7%
3 3
16.7%
8 3
16.7%
6 1
 
5.6%
1 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 18
52.9%
Latin 16
47.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 6
37.5%
S 2
 
12.5%
C 2
 
12.5%
M 2
 
12.5%
W 1
 
6.2%
I 1
 
6.2%
E 1
 
6.2%
U 1
 
6.2%
Common
ValueCountFrequency (%)
2 4
22.2%
0 3
16.7%
9 3
16.7%
3 3
16.7%
8 3
16.7%
6 1
 
5.6%
1 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 6
17.6%
2 4
11.8%
0 3
8.8%
9 3
8.8%
3 3
8.8%
8 3
8.8%
S 2
 
5.9%
C 2
 
5.9%
M 2
 
5.9%
6 1
 
2.9%
Other values (5) 5
14.7%

name_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.4 KiB
2023-12-09T22:47:45.554999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length56
Median length52
Mean length45.83333333
Min length29

Characters and Unicode

Total characters275
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSeth Low (I.S. 96) Magnet Program (Instrumental-Winds)
2nd rowThe Bay Academy (I.S. 98) Magnet Program (Science)
3rd rowDavid A. Boody (I.S. 228): Chinese Dual Language Program
4th rowMark Twain (I.S. 239) (Media)
5th rowJoseph B. Cavallaro (I.S. 281)
ValueCountFrequency (%)
i.s 6
 
14.3%
program 4
 
9.5%
magnet 3
 
7.1%
science 2
 
4.8%
joseph 1
 
2.4%
the 1
 
2.4%
eisenberg 1
 
2.4%
s 1
 
2.4%
herbert 1
 
2.4%
instrumental-winds 1
 
2.4%
Other values (21) 21
50.0%
2023-12-09T22:47:45.894645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
 
13.1%
e 20
 
7.3%
a 20
 
7.3%
. 15
 
5.5%
r 14
 
5.1%
n 12
 
4.4%
) 10
 
3.6%
g 10
 
3.6%
S 10
 
3.6%
( 10
 
3.6%
Other values (38) 118
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 143
52.0%
Uppercase Letter 43
 
15.6%
Space Separator 36
 
13.1%
Other Punctuation 16
 
5.8%
Decimal Number 16
 
5.8%
Close Punctuation 10
 
3.6%
Open Punctuation 10
 
3.6%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 20
14.0%
a 20
14.0%
r 14
9.8%
n 12
 
8.4%
g 10
 
7.0%
o 9
 
6.3%
i 8
 
5.6%
t 7
 
4.9%
m 6
 
4.2%
s 5
 
3.5%
Other values (11) 32
22.4%
Uppercase Letter
ValueCountFrequency (%)
S 10
23.3%
I 7
16.3%
M 5
11.6%
P 4
 
9.3%
B 3
 
7.0%
T 2
 
4.7%
A 2
 
4.7%
L 2
 
4.7%
D 2
 
4.7%
C 2
 
4.7%
Other values (4) 4
 
9.3%
Decimal Number
ValueCountFrequency (%)
2 4
25.0%
3 3
18.8%
9 3
18.8%
8 3
18.8%
6 1
 
6.2%
1 1
 
6.2%
0 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 15
93.8%
: 1
 
6.2%
Space Separator
ValueCountFrequency (%)
36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 186
67.6%
Common 89
32.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 20
 
10.8%
a 20
 
10.8%
r 14
 
7.5%
n 12
 
6.5%
g 10
 
5.4%
S 10
 
5.4%
o 9
 
4.8%
i 8
 
4.3%
I 7
 
3.8%
t 7
 
3.8%
Other values (25) 69
37.1%
Common
ValueCountFrequency (%)
36
40.4%
. 15
16.9%
) 10
 
11.2%
( 10
 
11.2%
2 4
 
4.5%
3 3
 
3.4%
9 3
 
3.4%
8 3
 
3.4%
- 1
 
1.1%
6 1
 
1.1%
Other values (3) 3
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
 
13.1%
e 20
 
7.3%
a 20
 
7.3%
. 15
 
5.5%
r 14
 
5.1%
n 12
 
4.4%
) 10
 
3.6%
g 10
 
3.6%
S 10
 
3.6%
( 10
 
3.6%
Other values (38) 118
42.9%

admissionsmethod_prog7
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:46.064837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length11
Min length4

Characters and Unicode

Total characters66
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowTalent Test
2nd rowTalent Test
3rd rowScreened: Language
4th rowTalent Test
5th rowOpen
ValueCountFrequency (%)
talent 4
36.4%
test 4
36.4%
open 1
 
9.1%
screened 1
 
9.1%
language 1
 
9.1%
2023-12-09T22:47:46.352188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 13
19.7%
T 8
12.1%
t 8
12.1%
n 7
10.6%
a 6
9.1%
5
 
7.6%
l 4
 
6.1%
s 4
 
6.1%
g 2
 
3.0%
d 1
 
1.5%
Other values (8) 8
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 49
74.2%
Uppercase Letter 11
 
16.7%
Space Separator 5
 
7.6%
Other Punctuation 1
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13
26.5%
t 8
16.3%
n 7
14.3%
a 6
12.2%
l 4
 
8.2%
s 4
 
8.2%
g 2
 
4.1%
d 1
 
2.0%
p 1
 
2.0%
r 1
 
2.0%
Other values (2) 2
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
T 8
72.7%
L 1
 
9.1%
S 1
 
9.1%
O 1
 
9.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60
90.9%
Common 6
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13
21.7%
T 8
13.3%
t 8
13.3%
n 7
11.7%
a 6
10.0%
l 4
 
6.7%
s 4
 
6.7%
g 2
 
3.3%
d 1
 
1.7%
L 1
 
1.7%
Other values (6) 6
10.0%
Common
ValueCountFrequency (%)
5
83.3%
: 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 13
19.7%
T 8
12.1%
t 8
12.1%
n 7
10.6%
a 6
9.1%
5
 
7.6%
l 4
 
6.1%
s 4
 
6.1%
g 2
 
3.0%
d 1
 
1.5%
Other values (8) 8
12.1%

geapps_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:46.533726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.833333333
Min length2

Characters and Unicode

Total characters17
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row22
2nd row492
3rd row122
4th row234
5th row641
ValueCountFrequency (%)
641 1
16.7%
492 1
16.7%
122 1
16.7%
22 1
16.7%
234 1
16.7%
126 1
16.7%
2023-12-09T22:47:46.830564image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7
41.2%
4 3
17.6%
1 3
17.6%
6 2
 
11.8%
9 1
 
5.9%
3 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 7
41.2%
4 3
17.6%
1 3
17.6%
6 2
 
11.8%
9 1
 
5.9%
3 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 7
41.2%
4 3
17.6%
1 3
17.6%
6 2
 
11.8%
9 1
 
5.9%
3 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 7
41.2%
4 3
17.6%
1 3
17.6%
6 2
 
11.8%
9 1
 
5.9%
3 1
 
5.9%

swdapps_prog7
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:46.974780image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length1.833333333
Min length1

Characters and Unicode

Total characters11
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row1
2nd row32
3rd row19
4th row32
5th row141
ValueCountFrequency (%)
32 2
33.3%
19 1
16.7%
141 1
16.7%
1 1
16.7%
8 1
16.7%
2023-12-09T22:47:47.253330image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
36.4%
3 2
18.2%
2 2
18.2%
9 1
 
9.1%
4 1
 
9.1%
8 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
36.4%
3 2
18.2%
2 2
18.2%
9 1
 
9.1%
4 1
 
9.1%
8 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
36.4%
3 2
18.2%
2 2
18.2%
9 1
 
9.1%
4 1
 
9.1%
8 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
36.4%
3 2
18.2%
2 2
18.2%
9 1
 
9.1%
4 1
 
9.1%
8 1
 
9.1%

geseats_prog7
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:47.397596image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.166666667
Min length2

Characters and Unicode

Total characters13
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row24
2nd row57
3rd row24
4th row19
5th row185
ValueCountFrequency (%)
24 2
33.3%
19 1
16.7%
23 1
16.7%
57 1
16.7%
185 1
16.7%
2023-12-09T22:47:47.658233image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
23.1%
4 2
15.4%
1 2
15.4%
5 2
15.4%
9 1
 
7.7%
3 1
 
7.7%
7 1
 
7.7%
8 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
23.1%
4 2
15.4%
1 2
15.4%
5 2
15.4%
9 1
 
7.7%
3 1
 
7.7%
7 1
 
7.7%
8 1
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Common 13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
23.1%
4 2
15.4%
1 2
15.4%
5 2
15.4%
9 1
 
7.7%
3 1
 
7.7%
7 1
 
7.7%
8 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
23.1%
4 2
15.4%
1 2
15.4%
5 2
15.4%
9 1
 
7.7%
3 1
 
7.7%
7 1
 
7.7%
8 1
 
7.7%

swdseats_prog7
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:47.790893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row3
2nd row14
3rd row6
4th row5
5th row42
ValueCountFrequency (%)
5 2
33.3%
3 1
16.7%
6 1
16.7%
42 1
16.7%
14 1
16.7%
2023-12-09T22:47:48.033384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
3 1
12.5%
6 1
12.5%
2 1
12.5%
1 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
3 1
12.5%
6 1
12.5%
2 1
12.5%
1 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
3 1
12.5%
6 1
12.5%
2 1
12.5%
1 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
3 1
12.5%
6 1
12.5%
2 1
12.5%
1 1
12.5%

geappsperseat_prog7
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:48.160127image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.166666667
Min length1

Characters and Unicode

Total characters7
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row1
2nd row9
3rd row5
4th row12
5th row3
ValueCountFrequency (%)
5 2
33.3%
12 1
16.7%
1 1
16.7%
3 1
16.7%
9 1
16.7%
2023-12-09T22:47:48.400995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
28.6%
1 2
28.6%
2 1
14.3%
3 1
14.3%
9 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
28.6%
1 2
28.6%
2 1
14.3%
3 1
14.3%
9 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
28.6%
1 2
28.6%
2 1
14.3%
3 1
14.3%
9 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
28.6%
1 2
28.6%
2 1
14.3%
3 1
14.3%
9 1
14.3%

swdappsperseat_prog7
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:48.533081image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row0
2nd row2
3rd row3
4th row6
5th row3
ValueCountFrequency (%)
3 2
33.3%
2 2
33.3%
0 1
16.7%
6 1
16.7%
2023-12-09T22:47:48.774316image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
33.3%
2 2
33.3%
0 1
16.7%
6 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2
33.3%
2 2
33.3%
0 1
16.7%
6 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2
33.3%
2 2
33.3%
0 1
16.7%
6 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
33.3%
2 2
33.3%
0 1
16.7%
6 1
16.7%

gefilled_prog7
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:48.881745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowY
5th rowY
ValueCountFrequency (%)
y 4
66.7%
n 2
33.3%
2023-12-09T22:47:49.099110image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 4
66.7%
N 2
33.3%

swdfilled_prog7
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:47:49.203819image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
3rd rowN
4th rowY
5th rowY
ValueCountFrequency (%)
n 4
66.7%
y 2
33.3%
2023-12-09T22:47:49.414666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 4
66.7%
Y 2
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 4
66.7%
Y 2
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 4
66.7%
Y 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 4
66.7%
Y 2
33.3%

eligibility_prog7
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.3 KiB
2023-12-09T22:47:49.595796image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length42.16666667
Min length31

Characters and Unicode

Total characters253
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of District 21
3rd rowOpen to students and residents of Brooklyn
4th rowOpen to New York City residents
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 6
13.3%
to 6
13.3%
residents 6
13.3%
students 5
11.1%
and 5
11.1%
of 5
11.1%
district 4
8.9%
21 4
8.9%
brooklyn 1
 
2.2%
new 1
 
2.2%
Other values (2) 2
 
4.4%
2023-12-09T22:47:49.901621image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 192
75.9%
Space Separator 39
 
15.4%
Uppercase Letter 14
 
5.5%
Decimal Number 8
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 31
16.1%
s 26
13.5%
e 24
12.5%
n 23
12.0%
d 16
8.3%
i 15
7.8%
o 14
7.3%
r 12
 
6.2%
p 6
 
3.1%
f 5
 
2.6%
Other values (7) 20
10.4%
Uppercase Letter
ValueCountFrequency (%)
O 6
42.9%
D 4
28.6%
B 1
 
7.1%
N 1
 
7.1%
Y 1
 
7.1%
C 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 206
81.4%
Common 47
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 31
15.0%
s 26
12.6%
e 24
11.7%
n 23
11.2%
d 16
7.8%
i 15
7.3%
o 14
6.8%
r 12
 
5.8%
O 6
 
2.9%
p 6
 
2.9%
Other values (13) 33
16.0%
Common
ValueCountFrequency (%)
39
83.0%
2 4
 
8.5%
1 4
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

priority1_prog7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:47:50.085611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPriority to residents of the middle school zone
ValueCountFrequency (%)
priority 1
12.5%
to 1
12.5%
residents 1
12.5%
of 1
12.5%
the 1
12.5%
middle 1
12.5%
school 1
12.5%
zone 1
12.5%
2023-12-09T22:47:50.379411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
83.0%
Space Separator 7
 
14.9%
Uppercase Letter 1
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
15.4%
e 5
12.8%
i 4
10.3%
t 4
10.3%
s 3
7.7%
r 3
7.7%
d 3
7.7%
n 2
 
5.1%
l 2
 
5.1%
h 2
 
5.1%
Other values (5) 5
12.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
85.1%
Common 7
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
e 5
12.5%
i 4
10.0%
t 4
10.0%
s 3
7.5%
r 3
7.5%
d 3
7.5%
n 2
 
5.0%
l 2
 
5.0%
h 2
 
5.0%
Other values (6) 6
15.0%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

priority2_prog7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:47:50.564249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to District 21 students and residents
ValueCountFrequency (%)
then 1
14.3%
to 1
14.3%
district 1
14.3%
21 1
14.3%
students 1
14.3%
and 1
14.3%
residents 1
14.3%
2023-12-09T22:47:50.856347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
76.2%
Space Separator 6
 
14.3%
Decimal Number 2
 
4.8%
Uppercase Letter 2
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
18.8%
s 5
15.6%
e 4
12.5%
n 4
12.5%
i 3
9.4%
d 3
9.4%
r 2
 
6.2%
u 1
 
3.1%
c 1
 
3.1%
h 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
81.0%
Common 8
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
i 3
8.8%
d 3
8.8%
r 2
 
5.9%
u 1
 
2.9%
T 1
 
2.9%
c 1
 
2.9%
Other values (4) 4
11.8%
Common
ValueCountFrequency (%)
6
75.0%
2 1
 
12.5%
1 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

priority3_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:51.041579image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.6
Min length5

Characters and Unicode

Total characters28
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowK098ST
2nd rowK228N
3rd rowK239SC
4th rowK281VO
5th rowK303U
ValueCountFrequency (%)
k239sc 1
20.0%
k228n 1
20.0%
k098st 1
20.0%
k303u 1
20.0%
k281vo 1
20.0%
2023-12-09T22:47:51.347652image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 5
17.9%
2 4
14.3%
3 3
10.7%
8 3
10.7%
9 2
 
7.1%
S 2
 
7.1%
0 2
 
7.1%
C 1
 
3.6%
N 1
 
3.6%
T 1
 
3.6%
Other values (4) 4
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
53.6%
Uppercase Letter 13
46.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 5
38.5%
S 2
 
15.4%
C 1
 
7.7%
N 1
 
7.7%
T 1
 
7.7%
U 1
 
7.7%
V 1
 
7.7%
O 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 4
26.7%
3 3
20.0%
8 3
20.0%
9 2
13.3%
0 2
13.3%
1 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15
53.6%
Latin 13
46.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 5
38.5%
S 2
 
15.4%
C 1
 
7.7%
N 1
 
7.7%
T 1
 
7.7%
U 1
 
7.7%
V 1
 
7.7%
O 1
 
7.7%
Common
ValueCountFrequency (%)
2 4
26.7%
3 3
20.0%
8 3
20.0%
9 2
13.3%
0 2
13.3%
1 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 5
17.9%
2 4
14.3%
3 3
10.7%
8 3
10.7%
9 2
 
7.1%
S 2
 
7.1%
0 2
 
7.1%
C 1
 
3.6%
N 1
 
3.6%
T 1
 
3.6%
Other values (4) 4
14.3%

name_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.3 KiB
2023-12-09T22:47:51.573637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length59
Mean length54.6
Min length31

Characters and Unicode

Total characters273
Distinct characters50
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowThe Bay Academy (I.S. 98) Magnet Program (Instrumental - Strings)
2nd rowDavid A. Boody (I.S. 228): Russian Dual Language Program
3rd rowMark Twain (I.S. 239) (Science)
4th rowJoseph B. Cavallaro (I.S. 281) Magnet Program (Vocal Music)
5th rowHerbert S. Eisenberg (I.S. 303) Academy for Career Exploration
ValueCountFrequency (%)
i.s 5
 
11.9%
program 3
 
7.1%
academy 2
 
4.8%
magnet 2
 
4.8%
239 1
 
2.4%
instrumental 1
 
2.4%
1
 
2.4%
strings 1
 
2.4%
mark 1
 
2.4%
twain 1
 
2.4%
Other values (24) 24
57.1%
2023-12-09T22:47:51.932817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
13.6%
a 22
 
8.1%
r 17
 
6.2%
e 16
 
5.9%
. 13
 
4.8%
n 11
 
4.0%
o 11
 
4.0%
g 9
 
3.3%
( 8
 
2.9%
S 8
 
2.9%
Other values (40) 121
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 151
55.3%
Uppercase Letter 40
 
14.7%
Space Separator 37
 
13.6%
Other Punctuation 14
 
5.1%
Decimal Number 14
 
5.1%
Open Punctuation 8
 
2.9%
Close Punctuation 8
 
2.9%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 22
14.6%
r 17
11.3%
e 16
10.6%
n 11
 
7.3%
o 11
 
7.3%
g 9
 
6.0%
i 8
 
5.3%
t 7
 
4.6%
s 7
 
4.6%
c 6
 
4.0%
Other values (13) 37
24.5%
Uppercase Letter
ValueCountFrequency (%)
S 8
20.0%
I 6
15.0%
M 4
10.0%
P 3
 
7.5%
B 3
 
7.5%
A 3
 
7.5%
E 2
 
5.0%
T 2
 
5.0%
D 2
 
5.0%
C 2
 
5.0%
Other values (5) 5
12.5%
Decimal Number
ValueCountFrequency (%)
2 4
28.6%
3 3
21.4%
8 3
21.4%
9 2
14.3%
1 1
 
7.1%
0 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 13
92.9%
: 1
 
7.1%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 191
70.0%
Common 82
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 22
 
11.5%
r 17
 
8.9%
e 16
 
8.4%
n 11
 
5.8%
o 11
 
5.8%
g 9
 
4.7%
S 8
 
4.2%
i 8
 
4.2%
t 7
 
3.7%
s 7
 
3.7%
Other values (28) 75
39.3%
Common
ValueCountFrequency (%)
37
45.1%
. 13
 
15.9%
( 8
 
9.8%
) 8
 
9.8%
2 4
 
4.9%
3 3
 
3.7%
8 3
 
3.7%
9 2
 
2.4%
1 1
 
1.2%
0 1
 
1.2%
Other values (2) 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
 
13.6%
a 22
 
8.1%
r 17
 
6.2%
e 16
 
5.9%
. 13
 
4.8%
n 11
 
4.0%
o 11
 
4.0%
g 9
 
3.3%
( 8
 
2.9%
S 8
 
2.9%
Other values (40) 121
44.3%

admissionsmethod_prog8
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:52.101471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length11
Min length4

Characters and Unicode

Total characters55
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st rowTalent Test
2nd rowScreened: Language
3rd rowTalent Test
4th rowTalent Test
5th rowOpen
ValueCountFrequency (%)
talent 3
33.3%
test 3
33.3%
open 1
 
11.1%
screened 1
 
11.1%
language 1
 
11.1%
2023-12-09T22:47:52.391191image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11
20.0%
T 6
10.9%
n 6
10.9%
t 6
10.9%
a 5
9.1%
4
 
7.3%
l 3
 
5.5%
s 3
 
5.5%
g 2
 
3.6%
d 1
 
1.8%
Other values (8) 8
14.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41
74.5%
Uppercase Letter 9
 
16.4%
Space Separator 4
 
7.3%
Other Punctuation 1
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
26.8%
n 6
14.6%
t 6
14.6%
a 5
12.2%
l 3
 
7.3%
s 3
 
7.3%
g 2
 
4.9%
d 1
 
2.4%
p 1
 
2.4%
r 1
 
2.4%
Other values (2) 2
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
T 6
66.7%
L 1
 
11.1%
S 1
 
11.1%
O 1
 
11.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 50
90.9%
Common 5
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
22.0%
T 6
12.0%
n 6
12.0%
t 6
12.0%
a 5
10.0%
l 3
 
6.0%
s 3
 
6.0%
g 2
 
4.0%
d 1
 
2.0%
L 1
 
2.0%
Other values (6) 6
12.0%
Common
ValueCountFrequency (%)
4
80.0%
: 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 11
20.0%
T 6
10.9%
n 6
10.9%
t 6
10.9%
a 5
9.1%
4
 
7.3%
l 3
 
5.5%
s 3
 
5.5%
g 2
 
3.6%
d 1
 
1.8%
Other values (8) 8
14.5%

geapps_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:52.564386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8
Min length2

Characters and Unicode

Total characters14
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row78
2nd row261
3rd row1095
4th row42
5th row215
ValueCountFrequency (%)
261 1
20.0%
1095 1
20.0%
42 1
20.0%
215 1
20.0%
78 1
20.0%
2023-12-09T22:47:52.860662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
21.4%
1 3
21.4%
5 2
14.3%
6 1
 
7.1%
0 1
 
7.1%
9 1
 
7.1%
4 1
 
7.1%
7 1
 
7.1%
8 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
21.4%
1 3
21.4%
5 2
14.3%
6 1
 
7.1%
0 1
 
7.1%
9 1
 
7.1%
4 1
 
7.1%
7 1
 
7.1%
8 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
21.4%
1 3
21.4%
5 2
14.3%
6 1
 
7.1%
0 1
 
7.1%
9 1
 
7.1%
4 1
 
7.1%
7 1
 
7.1%
8 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
21.4%
1 3
21.4%
5 2
14.3%
6 1
 
7.1%
0 1
 
7.1%
9 1
 
7.1%
4 1
 
7.1%
7 1
 
7.1%
8 1
 
7.1%

swdapps_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:53.025943image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8
Min length1

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row5
2nd row24
3rd row52
4th row11
5th row51
ValueCountFrequency (%)
11 1
20.0%
52 1
20.0%
5 1
20.0%
24 1
20.0%
51 1
20.0%
2023-12-09T22:47:53.313747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
33.3%
5 3
33.3%
2 2
22.2%
4 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
33.3%
5 3
33.3%
2 2
22.2%
4 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
33.3%
5 3
33.3%
2 2
22.2%
4 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
33.3%
5 3
33.3%
2 2
22.2%
4 1
 
11.1%

geseats_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:53.490187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row29
2nd row13
3rd row26
4th row24
5th row54
ValueCountFrequency (%)
24 1
20.0%
29 1
20.0%
26 1
20.0%
54 1
20.0%
13 1
20.0%
2023-12-09T22:47:53.774748image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
30.0%
4 2
20.0%
9 1
 
10.0%
6 1
 
10.0%
5 1
 
10.0%
1 1
 
10.0%
3 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
30.0%
4 2
20.0%
9 1
 
10.0%
6 1
 
10.0%
5 1
 
10.0%
1 1
 
10.0%
3 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
30.0%
4 2
20.0%
9 1
 
10.0%
6 1
 
10.0%
5 1
 
10.0%
1 1
 
10.0%
3 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
30.0%
4 2
20.0%
9 1
 
10.0%
6 1
 
10.0%
5 1
 
10.0%
1 1
 
10.0%
3 1
 
10.0%

swdseats_prog8
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:53.903202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row7
2nd row3
3rd row6
4th row6
5th row11
ValueCountFrequency (%)
6 2
40.0%
3 1
20.0%
11 1
20.0%
7 1
20.0%
2023-12-09T22:47:54.160832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2
33.3%
1 2
33.3%
3 1
16.7%
7 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2
33.3%
1 2
33.3%
3 1
16.7%
7 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2
33.3%
1 2
33.3%
3 1
16.7%
7 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2
33.3%
1 2
33.3%
3 1
16.7%
7 1
16.7%

geappsperseat_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:54.341518image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.4
Min length1

Characters and Unicode

Total characters7
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row3
2nd row20
3rd row42
4th row2
5th row4
ValueCountFrequency (%)
3 1
20.0%
20 1
20.0%
42 1
20.0%
4 1
20.0%
2 1
20.0%
2023-12-09T22:47:54.644959image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
42.9%
4 2
28.6%
3 1
 
14.3%
0 1
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
42.9%
4 2
28.6%
3 1
 
14.3%
0 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
42.9%
4 2
28.6%
3 1
 
14.3%
0 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
42.9%
4 2
28.6%
3 1
 
14.3%
0 1
 
14.3%

swdappsperseat_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:54.806415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row1
2nd row8
3rd row9
4th row2
5th row5
ValueCountFrequency (%)
1 1
20.0%
5 1
20.0%
9 1
20.0%
8 1
20.0%
2 1
20.0%
2023-12-09T22:47:55.089805image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
20.0%
5 1
20.0%
9 1
20.0%
8 1
20.0%
2 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
20.0%
5 1
20.0%
9 1
20.0%
8 1
20.0%
2 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
20.0%
5 1
20.0%
9 1
20.0%
8 1
20.0%
2 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
20.0%
5 1
20.0%
9 1
20.0%
8 1
20.0%
2 1
20.0%

gefilled_prog8
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:55.209026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowN
5th rowN
ValueCountFrequency (%)
y 3
60.0%
n 2
40.0%
2023-12-09T22:47:55.433153image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

swdfilled_prog8
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:47:55.542230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowY
4th rowN
5th rowY
ValueCountFrequency (%)
y 3
60.0%
n 2
40.0%
2023-12-09T22:47:55.764661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 3
60.0%
N 2
40.0%

eligibility_prog8
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.3 KiB
2023-12-09T22:47:55.956574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length41.6
Min length31

Characters and Unicode

Total characters208
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of Brooklyn
3rd rowOpen to New York City residents
4th rowOpen to students and residents of District 21
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 5
13.5%
to 5
13.5%
residents 5
13.5%
students 4
10.8%
and 4
10.8%
of 4
10.8%
district 3
8.1%
21 3
8.1%
brooklyn 1
 
2.7%
new 1
 
2.7%
Other values (2) 2
 
5.4%
2023-12-09T22:47:56.278493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
15.4%
t 25
12.0%
s 21
10.1%
e 20
9.6%
n 19
9.1%
d 13
 
6.2%
o 12
 
5.8%
i 12
 
5.8%
r 10
 
4.8%
O 5
 
2.4%
Other values (16) 39
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 158
76.0%
Space Separator 32
 
15.4%
Uppercase Letter 12
 
5.8%
Decimal Number 6
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 25
15.8%
s 21
13.3%
e 20
12.7%
n 19
12.0%
d 13
8.2%
o 12
7.6%
i 12
7.6%
r 10
 
6.3%
p 5
 
3.2%
f 4
 
2.5%
Other values (7) 17
10.8%
Uppercase Letter
ValueCountFrequency (%)
O 5
41.7%
D 3
25.0%
B 1
 
8.3%
N 1
 
8.3%
Y 1
 
8.3%
C 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 170
81.7%
Common 38
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 25
14.7%
s 21
12.4%
e 20
11.8%
n 19
11.2%
d 13
7.6%
o 12
7.1%
i 12
7.1%
r 10
 
5.9%
O 5
 
2.9%
p 5
 
2.9%
Other values (13) 28
16.5%
Common
ValueCountFrequency (%)
32
84.2%
2 3
 
7.9%
1 3
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 208
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
15.4%
t 25
12.0%
s 21
10.1%
e 20
9.6%
n 19
9.1%
d 13
 
6.2%
o 12
 
5.8%
i 12
 
5.8%
r 10
 
4.8%
O 5
 
2.4%
Other values (16) 39
18.8%

priority1_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:47:56.474468image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPriority to residents of the middle school zone
ValueCountFrequency (%)
priority 1
12.5%
to 1
12.5%
residents 1
12.5%
of 1
12.5%
the 1
12.5%
middle 1
12.5%
school 1
12.5%
zone 1
12.5%
2023-12-09T22:47:56.797081image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
83.0%
Space Separator 7
 
14.9%
Uppercase Letter 1
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
15.4%
e 5
12.8%
i 4
10.3%
t 4
10.3%
s 3
7.7%
r 3
7.7%
d 3
7.7%
n 2
 
5.1%
l 2
 
5.1%
h 2
 
5.1%
Other values (5) 5
12.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
85.1%
Common 7
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
e 5
12.5%
i 4
10.0%
t 4
10.0%
s 3
7.5%
r 3
7.5%
d 3
7.5%
n 2
 
5.0%
l 2
 
5.0%
h 2
 
5.0%
Other values (6) 6
15.0%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

priority2_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:47:56.992415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to District 21 students and residents
ValueCountFrequency (%)
then 1
14.3%
to 1
14.3%
district 1
14.3%
21 1
14.3%
students 1
14.3%
and 1
14.3%
residents 1
14.3%
2023-12-09T22:47:57.312624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
76.2%
Space Separator 6
 
14.3%
Decimal Number 2
 
4.8%
Uppercase Letter 2
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
18.8%
s 5
15.6%
e 4
12.5%
n 4
12.5%
i 3
9.4%
d 3
9.4%
r 2
 
6.2%
u 1
 
3.1%
c 1
 
3.1%
h 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
81.0%
Common 8
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
i 3
8.8%
d 3
8.8%
r 2
 
5.9%
u 1
 
2.9%
T 1
 
2.9%
c 1
 
2.9%
Other values (4) 4
11.8%
Common
ValueCountFrequency (%)
6
75.0%
2 1
 
12.5%
1 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

priority3_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog9
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.1 KiB
2023-12-09T22:47:57.499388image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.75
Min length5

Characters and Unicode

Total characters23
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowK098VO
2nd rowK228P
3rd rowK239ST
4th rowK303VO
ValueCountFrequency (%)
k098vo 1
25.0%
k239st 1
25.0%
k303vo 1
25.0%
k228p 1
25.0%
2023-12-09T22:47:57.811467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 4
17.4%
2 3
13.0%
3 3
13.0%
0 2
8.7%
9 2
8.7%
8 2
8.7%
V 2
8.7%
O 2
8.7%
S 1
 
4.3%
T 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
52.2%
Uppercase Letter 11
47.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 4
36.4%
V 2
18.2%
O 2
18.2%
S 1
 
9.1%
T 1
 
9.1%
P 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 3
25.0%
3 3
25.0%
0 2
16.7%
9 2
16.7%
8 2
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 12
52.2%
Latin 11
47.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 4
36.4%
V 2
18.2%
O 2
18.2%
S 1
 
9.1%
T 1
 
9.1%
P 1
 
9.1%
Common
ValueCountFrequency (%)
2 3
25.0%
3 3
25.0%
0 2
16.7%
9 2
16.7%
8 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 4
17.4%
2 3
13.0%
3 3
13.0%
0 2
8.7%
9 2
8.7%
8 2
8.7%
V 2
8.7%
O 2
8.7%
S 1
 
4.3%
T 1
 
4.3%

name_prog9
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.2 KiB
2023-12-09T22:47:58.039937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length60
Median length55
Mean length53
Min length42

Characters and Unicode

Total characters212
Distinct characters43
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowThe Bay Academy (I.S. 98) Magnet Program (Vocal Music)
2nd rowDavid A. Boody (I.S. 228): Spanish Dual Language Program
3rd rowMark Twain (I.S. 239) (String Instruments)
4th rowHerbert S. Eisenberg (I.S. 303) Magnet Program (Vocal Music)
ValueCountFrequency (%)
i.s 4
 
12.1%
program 3
 
9.1%
magnet 2
 
6.1%
vocal 2
 
6.1%
music 2
 
6.1%
herbert 1
 
3.0%
239 1
 
3.0%
dual 1
 
3.0%
spanish 1
 
3.0%
228 1
 
3.0%
Other values (15) 15
45.5%
2023-12-09T22:47:58.416145image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
13.7%
a 16
 
7.5%
r 12
 
5.7%
e 10
 
4.7%
. 10
 
4.7%
g 9
 
4.2%
n 9
 
4.2%
i 7
 
3.3%
( 7
 
3.3%
o 7
 
3.3%
Other values (33) 96
45.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 114
53.8%
Uppercase Letter 33
 
15.6%
Space Separator 29
 
13.7%
Other Punctuation 11
 
5.2%
Decimal Number 11
 
5.2%
Open Punctuation 7
 
3.3%
Close Punctuation 7
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 16
14.0%
r 12
10.5%
e 10
 
8.8%
g 9
 
7.9%
n 9
 
7.9%
i 7
 
6.1%
o 7
 
6.1%
s 6
 
5.3%
t 6
 
5.3%
m 5
 
4.4%
Other values (11) 27
23.7%
Uppercase Letter
ValueCountFrequency (%)
S 7
21.2%
M 5
15.2%
I 5
15.2%
P 3
9.1%
B 2
 
6.1%
A 2
 
6.1%
T 2
 
6.1%
V 2
 
6.1%
D 2
 
6.1%
H 1
 
3.0%
Other values (2) 2
 
6.1%
Decimal Number
ValueCountFrequency (%)
2 3
27.3%
3 3
27.3%
8 2
18.2%
9 2
18.2%
0 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 10
90.9%
: 1
 
9.1%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 147
69.3%
Common 65
30.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 16
 
10.9%
r 12
 
8.2%
e 10
 
6.8%
g 9
 
6.1%
n 9
 
6.1%
i 7
 
4.8%
o 7
 
4.8%
S 7
 
4.8%
s 6
 
4.1%
t 6
 
4.1%
Other values (23) 58
39.5%
Common
ValueCountFrequency (%)
29
44.6%
. 10
 
15.4%
( 7
 
10.8%
) 7
 
10.8%
2 3
 
4.6%
3 3
 
4.6%
8 2
 
3.1%
9 2
 
3.1%
: 1
 
1.5%
0 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
 
13.7%
a 16
 
7.5%
r 12
 
5.7%
e 10
 
4.7%
. 10
 
4.7%
g 9
 
4.2%
n 9
 
4.2%
i 7
 
3.3%
( 7
 
3.3%
o 7
 
3.3%
Other values (33) 96
45.3%

admissionsmethod_prog9
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing470
Missing (%)99.2%
Memory size15.1 KiB
2023-12-09T22:47:58.597889image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length12.75
Min length11

Characters and Unicode

Total characters51
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowTalent Test
2nd rowScreened: Language
3rd rowTalent Test
4th rowTalent Test
ValueCountFrequency (%)
talent 3
37.5%
test 3
37.5%
screened 1
 
12.5%
language 1
 
12.5%
2023-12-09T22:47:58.912665image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 10
19.6%
T 6
11.8%
t 6
11.8%
a 5
9.8%
n 5
9.8%
4
 
7.8%
l 3
 
5.9%
s 3
 
5.9%
g 2
 
3.9%
S 1
 
2.0%
Other values (6) 6
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38
74.5%
Uppercase Letter 8
 
15.7%
Space Separator 4
 
7.8%
Other Punctuation 1
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 10
26.3%
t 6
15.8%
a 5
13.2%
n 5
13.2%
l 3
 
7.9%
s 3
 
7.9%
g 2
 
5.3%
c 1
 
2.6%
r 1
 
2.6%
d 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
T 6
75.0%
S 1
 
12.5%
L 1
 
12.5%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46
90.2%
Common 5
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10
21.7%
T 6
13.0%
t 6
13.0%
a 5
10.9%
n 5
10.9%
l 3
 
6.5%
s 3
 
6.5%
g 2
 
4.3%
S 1
 
2.2%
c 1
 
2.2%
Other values (4) 4
 
8.7%
Common
ValueCountFrequency (%)
4
80.0%
: 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 10
19.6%
T 6
11.8%
t 6
11.8%
a 5
9.8%
n 5
9.8%
4
 
7.8%
l 3
 
5.9%
s 3
 
5.9%
g 2
 
3.9%
S 1
 
2.0%
Other values (6) 6
11.8%

geapps_prog9
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:47:59.086032image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row90
2nd row173
3rd row237
4th row24
ValueCountFrequency (%)
90 1
25.0%
237 1
25.0%
173 1
25.0%
24 1
25.0%
2023-12-09T22:48:00.077937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
20.0%
3 2
20.0%
7 2
20.0%
9 1
10.0%
0 1
10.0%
1 1
10.0%
4 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
20.0%
3 2
20.0%
7 2
20.0%
9 1
10.0%
0 1
10.0%
1 1
10.0%
4 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
20.0%
3 2
20.0%
7 2
20.0%
9 1
10.0%
0 1
10.0%
1 1
10.0%
4 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
20.0%
3 2
20.0%
7 2
20.0%
9 1
10.0%
0 1
10.0%
1 1
10.0%
4 1
10.0%

swdapps_prog9
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:48:00.244362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.75
Min length1

Characters and Unicode

Total characters7
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row15
2nd row30
3rd row12
4th row2
ValueCountFrequency (%)
12 1
25.0%
15 1
25.0%
30 1
25.0%
2 1
25.0%
2023-12-09T22:48:00.539139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
28.6%
2 2
28.6%
5 1
14.3%
3 1
14.3%
0 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
28.6%
2 2
28.6%
5 1
14.3%
3 1
14.3%
0 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
28.6%
2 2
28.6%
5 1
14.3%
3 1
14.3%
0 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
28.6%
2 2
28.6%
5 1
14.3%
3 1
14.3%
0 1
14.3%

geseats_prog9
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:48:00.710948image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row27
2nd row12
3rd row26
4th row23
ValueCountFrequency (%)
12 1
25.0%
23 1
25.0%
26 1
25.0%
27 1
25.0%
2023-12-09T22:48:01.000335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
6 1
 
12.5%
7 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
6 1
 
12.5%
7 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
6 1
 
12.5%
7 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
6 1
 
12.5%
7 1
 
12.5%

swdseats_prog9
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:48:01.115757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row6
2nd row3
3rd row6
4th row5
ValueCountFrequency (%)
6 2
50.0%
3 1
25.0%
5 1
25.0%
2023-12-09T22:48:01.353194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2
50.0%
3 1
25.0%
5 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2
50.0%
3 1
25.0%
5 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2
50.0%
3 1
25.0%
5 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2
50.0%
3 1
25.0%
5 1
25.0%

geappsperseat_prog9
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:48:01.520020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.25
Min length1

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row3
2nd row14
3rd row9
4th row1
ValueCountFrequency (%)
1 1
25.0%
3 1
25.0%
9 1
25.0%
14 1
25.0%
2023-12-09T22:48:01.810756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
40.0%
3 1
20.0%
9 1
20.0%
4 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
40.0%
3 1
20.0%
9 1
20.0%
4 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
40.0%
3 1
20.0%
9 1
20.0%
4 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
40.0%
3 1
20.0%
9 1
20.0%
4 1
20.0%

swdappsperseat_prog9
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:48:01.972708image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.25
Min length1

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row3
2nd row10
3rd row2
4th row0
ValueCountFrequency (%)
3 1
25.0%
0 1
25.0%
10 1
25.0%
2 1
25.0%
2023-12-09T22:48:02.265017image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
40.0%
3 1
20.0%
1 1
20.0%
2 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
40.0%
3 1
20.0%
1 1
20.0%
2 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
40.0%
3 1
20.0%
1 1
20.0%
2 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
40.0%
3 1
20.0%
1 1
20.0%
2 1
20.0%

gefilled_prog9
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:48:02.383353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowN
ValueCountFrequency (%)
y 3
75.0%
n 1
 
25.0%
2023-12-09T22:48:02.613008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 3
75.0%
N 1
 
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 3
75.0%
N 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 3
75.0%
N 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 3
75.0%
N 1
 
25.0%

swdfilled_prog9
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:48:02.724167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowN
4th rowN
ValueCountFrequency (%)
n 2
50.0%
y 2
50.0%
2023-12-09T22:48:02.942076image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 2
50.0%
Y 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 2
50.0%
Y 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2
50.0%
Y 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 2
50.0%
Y 2
50.0%

eligibility_prog9
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.2 KiB
2023-12-09T22:48:03.139345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length43.5
Mean length40.75
Min length31

Characters and Unicode

Total characters163
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of Brooklyn
3rd rowOpen to New York City residents
4th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 4
13.8%
to 4
13.8%
residents 4
13.8%
students 3
10.3%
and 3
10.3%
of 3
10.3%
district 2
6.9%
21 2
6.9%
brooklyn 1
 
3.4%
new 1
 
3.4%
Other values (2) 2
6.9%
2023-12-09T22:48:03.484507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
15.3%
t 19
11.7%
e 16
9.8%
s 16
9.8%
n 15
9.2%
o 10
 
6.1%
d 10
 
6.1%
i 9
 
5.5%
r 8
 
4.9%
O 4
 
2.5%
Other values (16) 31
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 124
76.1%
Space Separator 25
 
15.3%
Uppercase Letter 10
 
6.1%
Decimal Number 4
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 19
15.3%
e 16
12.9%
s 16
12.9%
n 15
12.1%
o 10
8.1%
d 10
8.1%
i 9
7.3%
r 8
6.5%
p 4
 
3.2%
f 3
 
2.4%
Other values (7) 14
11.3%
Uppercase Letter
ValueCountFrequency (%)
O 4
40.0%
D 2
20.0%
B 1
 
10.0%
N 1
 
10.0%
Y 1
 
10.0%
C 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 134
82.2%
Common 29
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 19
14.2%
e 16
11.9%
s 16
11.9%
n 15
11.2%
o 10
7.5%
d 10
7.5%
i 9
 
6.7%
r 8
 
6.0%
O 4
 
3.0%
p 4
 
3.0%
Other values (13) 23
17.2%
Common
ValueCountFrequency (%)
25
86.2%
2 2
 
6.9%
1 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
15.3%
t 19
11.7%
e 16
9.8%
s 16
9.8%
n 15
9.2%
o 10
 
6.1%
d 10
 
6.1%
i 9
 
5.5%
r 8
 
4.9%
O 4
 
2.5%
Other values (16) 31
19.0%

priority1_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog10
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:03.660937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.666666667
Min length5

Characters and Unicode

Total characters17
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowK098WI
2nd rowK228Q
3rd rowK239VO
ValueCountFrequency (%)
k228q 1
33.3%
k098wi 1
33.3%
k239vo 1
33.3%
2023-12-09T22:48:03.953947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 3
17.6%
2 3
17.6%
8 2
11.8%
9 2
11.8%
Q 1
 
5.9%
0 1
 
5.9%
W 1
 
5.9%
I 1
 
5.9%
3 1
 
5.9%
V 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
52.9%
Uppercase Letter 8
47.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 3
37.5%
Q 1
 
12.5%
W 1
 
12.5%
I 1
 
12.5%
V 1
 
12.5%
O 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
8 2
22.2%
9 2
22.2%
0 1
 
11.1%
3 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
52.9%
Latin 8
47.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 3
37.5%
Q 1
 
12.5%
W 1
 
12.5%
I 1
 
12.5%
V 1
 
12.5%
O 1
 
12.5%
Common
ValueCountFrequency (%)
2 3
33.3%
8 2
22.2%
9 2
22.2%
0 1
 
11.1%
3 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 3
17.6%
2 3
17.6%
8 2
11.8%
9 2
11.8%
Q 1
 
5.9%
0 1
 
5.9%
W 1
 
5.9%
I 1
 
5.9%
3 1
 
5.9%
V 1
 
5.9%

name_prog10
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.2 KiB
2023-12-09T22:48:04.179893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length55
Mean length49
Min length29

Characters and Unicode

Total characters147
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowThe Bay Academy (I.S. 98) Magnet Program (Instrumental - Winds)
2nd rowDavid A. Boody (I.S. 228): Hebrew Dual Language Program
3rd rowMark Twain (I.S. 239) (Vocal)
ValueCountFrequency (%)
i.s 3
 
12.5%
program 2
 
8.3%
the 1
 
4.2%
boody 1
 
4.2%
239 1
 
4.2%
twain 1
 
4.2%
mark 1
 
4.2%
language 1
 
4.2%
dual 1
 
4.2%
hebrew 1
 
4.2%
Other values (11) 11
45.8%
2023-12-09T22:48:04.542313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
14.3%
a 13
 
8.8%
r 7
 
4.8%
e 7
 
4.8%
. 7
 
4.8%
n 6
 
4.1%
( 5
 
3.4%
g 5
 
3.4%
) 5
 
3.4%
o 5
 
3.4%
Other values (32) 66
44.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 76
51.7%
Uppercase Letter 23
 
15.6%
Space Separator 21
 
14.3%
Other Punctuation 8
 
5.4%
Decimal Number 8
 
5.4%
Open Punctuation 5
 
3.4%
Close Punctuation 5
 
3.4%
Dash Punctuation 1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 13
17.1%
r 7
 
9.2%
e 7
 
9.2%
n 6
 
7.9%
g 5
 
6.6%
o 5
 
6.6%
m 4
 
5.3%
d 4
 
5.3%
i 3
 
3.9%
l 3
 
3.9%
Other values (10) 19
25.0%
Uppercase Letter
ValueCountFrequency (%)
I 4
17.4%
S 3
13.0%
D 2
8.7%
T 2
8.7%
P 2
8.7%
B 2
8.7%
A 2
8.7%
M 2
8.7%
W 1
 
4.3%
H 1
 
4.3%
Other values (2) 2
8.7%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
9 2
25.0%
8 2
25.0%
3 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
: 1
 
12.5%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 99
67.3%
Common 48
32.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 13
 
13.1%
r 7
 
7.1%
e 7
 
7.1%
n 6
 
6.1%
g 5
 
5.1%
o 5
 
5.1%
m 4
 
4.0%
d 4
 
4.0%
I 4
 
4.0%
S 3
 
3.0%
Other values (22) 41
41.4%
Common
ValueCountFrequency (%)
21
43.8%
. 7
 
14.6%
( 5
 
10.4%
) 5
 
10.4%
2 3
 
6.2%
9 2
 
4.2%
8 2
 
4.2%
- 1
 
2.1%
: 1
 
2.1%
3 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
 
14.3%
a 13
 
8.8%
r 7
 
4.8%
e 7
 
4.8%
. 7
 
4.8%
n 6
 
4.1%
( 5
 
3.4%
g 5
 
3.4%
) 5
 
3.4%
o 5
 
3.4%
Other values (32) 66
44.9%

admissionsmethod_prog10
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:04.725418image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length13.33333333
Min length11

Characters and Unicode

Total characters40
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowTalent Test
2nd rowScreened: Language
3rd rowTalent Test
ValueCountFrequency (%)
talent 2
33.3%
test 2
33.3%
screened 1
16.7%
language 1
16.7%
2023-12-09T22:48:05.034155image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 8
20.0%
T 4
10.0%
a 4
10.0%
n 4
10.0%
t 4
10.0%
3
 
7.5%
l 2
 
5.0%
s 2
 
5.0%
g 2
 
5.0%
S 1
 
2.5%
Other values (6) 6
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30
75.0%
Uppercase Letter 6
 
15.0%
Space Separator 3
 
7.5%
Other Punctuation 1
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
26.7%
a 4
13.3%
n 4
13.3%
t 4
13.3%
l 2
 
6.7%
s 2
 
6.7%
g 2
 
6.7%
c 1
 
3.3%
r 1
 
3.3%
d 1
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
T 4
66.7%
S 1
 
16.7%
L 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
90.0%
Common 4
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8
22.2%
T 4
11.1%
a 4
11.1%
n 4
11.1%
t 4
11.1%
l 2
 
5.6%
s 2
 
5.6%
g 2
 
5.6%
S 1
 
2.8%
c 1
 
2.8%
Other values (4) 4
11.1%
Common
ValueCountFrequency (%)
3
75.0%
: 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8
20.0%
T 4
10.0%
a 4
10.0%
n 4
10.0%
t 4
10.0%
3
 
7.5%
l 2
 
5.0%
s 2
 
5.0%
g 2
 
5.0%
S 1
 
2.5%
Other values (6) 6
15.0%

geapps_prog10
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:05.203111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.333333333
Min length2

Characters and Unicode

Total characters7
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row73
2nd row35
3rd row318
ValueCountFrequency (%)
318 1
33.3%
73 1
33.3%
35 1
33.3%
2023-12-09T22:48:05.491002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3
42.9%
1 1
 
14.3%
8 1
 
14.3%
7 1
 
14.3%
5 1
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3
42.9%
1 1
 
14.3%
8 1
 
14.3%
7 1
 
14.3%
5 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 3
42.9%
1 1
 
14.3%
8 1
 
14.3%
7 1
 
14.3%
5 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 3
42.9%
1 1
 
14.3%
8 1
 
14.3%
7 1
 
14.3%
5 1
 
14.3%

swdapps_prog10
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:05.665612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row3
2nd row9
3rd row29
ValueCountFrequency (%)
3 1
33.3%
29 1
33.3%
9 1
33.3%
2023-12-09T22:48:05.965142image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 2
50.0%
3 1
25.0%
2 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 2
50.0%
3 1
25.0%
2 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 2
50.0%
3 1
25.0%
2 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 2
50.0%
3 1
25.0%
2 1
25.0%

geseats_prog10
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:06.145514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.666666667
Min length1

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row35
2nd row0
3rd row23
ValueCountFrequency (%)
0 1
33.3%
23 1
33.3%
35 1
33.3%
2023-12-09T22:48:06.452055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
40.0%
0 1
20.0%
2 1
20.0%
5 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2
40.0%
0 1
20.0%
2 1
20.0%
5 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2
40.0%
0 1
20.0%
2 1
20.0%
5 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
40.0%
0 1
20.0%
2 1
20.0%
5 1
20.0%

swdseats_prog10
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:06.619334image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row8
2nd row0
3rd row5
ValueCountFrequency (%)
0 1
33.3%
5 1
33.3%
8 1
33.3%
2023-12-09T22:48:06.862593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
33.3%
5 1
33.3%
8 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
33.3%
5 1
33.3%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
33.3%
5 1
33.3%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
33.3%
5 1
33.3%
8 1
33.3%

geappsperseat_prog10
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:06.993901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1.5
Mean length1.5
Min length1

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2
2nd row14
ValueCountFrequency (%)
14 1
50.0%
2 1
50.0%
2023-12-09T22:48:07.240047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
2 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
2 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
2 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
2 1
33.3%

swdappsperseat_prog10
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:07.349060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row0
2nd row6
ValueCountFrequency (%)
0 1
50.0%
6 1
50.0%
2023-12-09T22:48:07.572384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
50.0%
6 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
50.0%
6 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
50.0%
6 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
50.0%
6 1
50.0%

gefilled_prog10
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:07.683128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowN
2nd rowY
3rd rowY
ValueCountFrequency (%)
y 2
66.7%
n 1
33.3%
2023-12-09T22:48:07.903012image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

swdfilled_prog10
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:48:08.005574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowN
2nd rowY
3rd rowY
ValueCountFrequency (%)
y 2
66.7%
n 1
33.3%
2023-12-09T22:48:08.223525image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 2
66.7%
N 1
33.3%

eligibility_prog10
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.1 KiB
2023-12-09T22:48:08.413524image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length42
Mean length39.33333333
Min length31

Characters and Unicode

Total characters118
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of Brooklyn
3rd rowOpen to New York City residents
ValueCountFrequency (%)
open 3
14.3%
to 3
14.3%
residents 3
14.3%
students 2
9.5%
and 2
9.5%
of 2
9.5%
district 1
 
4.8%
21 1
 
4.8%
brooklyn 1
 
4.8%
new 1
 
4.8%
Other values (2) 2
9.5%
2023-12-09T22:48:08.734057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
15.3%
t 13
11.0%
e 12
10.2%
n 11
9.3%
s 11
9.3%
o 8
 
6.8%
d 7
 
5.9%
r 6
 
5.1%
i 6
 
5.1%
O 3
 
2.5%
Other values (16) 23
19.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 90
76.3%
Space Separator 18
 
15.3%
Uppercase Letter 8
 
6.8%
Decimal Number 2
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 13
14.4%
e 12
13.3%
n 11
12.2%
s 11
12.2%
o 8
8.9%
d 7
7.8%
r 6
6.7%
i 6
6.7%
p 3
 
3.3%
y 2
 
2.2%
Other values (7) 11
12.2%
Uppercase Letter
ValueCountFrequency (%)
O 3
37.5%
D 1
 
12.5%
B 1
 
12.5%
N 1
 
12.5%
Y 1
 
12.5%
C 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 98
83.1%
Common 20
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 13
13.3%
e 12
12.2%
n 11
11.2%
s 11
11.2%
o 8
8.2%
d 7
 
7.1%
r 6
 
6.1%
i 6
 
6.1%
O 3
 
3.1%
p 3
 
3.1%
Other values (13) 18
18.4%
Common
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
1 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
15.3%
t 13
11.0%
e 12
10.2%
n 11
9.3%
s 11
9.3%
o 8
 
6.8%
d 7
 
5.9%
r 6
 
5.1%
i 6
 
5.1%
O 3
 
2.5%
Other values (16) 23
19.5%

priority1_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:08.893013image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowK228SC
2nd rowK239WI
ValueCountFrequency (%)
k239wi 1
50.0%
k228sc 1
50.0%
2023-12-09T22:48:09.170176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
25.0%
K 2
16.7%
3 1
 
8.3%
9 1
 
8.3%
W 1
 
8.3%
I 1
 
8.3%
8 1
 
8.3%
S 1
 
8.3%
C 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
50.0%
Uppercase Letter 6
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 2
33.3%
W 1
16.7%
I 1
16.7%
S 1
16.7%
C 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
3 1
 
16.7%
9 1
 
16.7%
8 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
50.0%
Latin 6
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 2
33.3%
W 1
16.7%
I 1
16.7%
S 1
16.7%
C 1
16.7%
Common
ValueCountFrequency (%)
2 3
50.0%
3 1
 
16.7%
9 1
 
16.7%
8 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
25.0%
K 2
16.7%
3 1
 
8.3%
9 1
 
8.3%
W 1
 
8.3%
I 1
 
8.3%
8 1
 
8.3%
S 1
 
8.3%
C 1
 
8.3%

name_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.1 KiB
2023-12-09T22:48:09.362382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length50
Median length45
Mean length45
Min length40

Characters and Unicode

Total characters90
Distinct characters34
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Science)
2nd rowMark Twain (I.S. 239) (Wind Instruments)
ValueCountFrequency (%)
i.s 2
14.3%
mark 1
 
7.1%
twain 1
 
7.1%
239 1
 
7.1%
wind 1
 
7.1%
instruments 1
 
7.1%
david 1
 
7.1%
a 1
 
7.1%
boody 1
 
7.1%
228 1
 
7.1%
Other values (3) 3
21.4%
2023-12-09T22:48:09.678143image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
13.3%
n 6
 
6.7%
a 5
 
5.6%
. 5
 
5.6%
( 4
 
4.4%
r 4
 
4.4%
) 4
 
4.4%
e 4
 
4.4%
i 4
 
4.4%
S 3
 
3.3%
Other values (24) 39
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 45
50.0%
Uppercase Letter 14
 
15.6%
Space Separator 12
 
13.3%
Decimal Number 6
 
6.7%
Other Punctuation 5
 
5.6%
Open Punctuation 4
 
4.4%
Close Punctuation 4
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 6
13.3%
a 5
11.1%
r 4
8.9%
e 4
8.9%
i 4
8.9%
t 3
 
6.7%
d 3
 
6.7%
o 3
 
6.7%
m 2
 
4.4%
s 2
 
4.4%
Other values (7) 9
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
21.4%
I 3
21.4%
M 2
14.3%
D 1
 
7.1%
A 1
 
7.1%
B 1
 
7.1%
T 1
 
7.1%
P 1
 
7.1%
W 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
9 1
 
16.7%
3 1
 
16.7%
8 1
 
16.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 59
65.6%
Common 31
34.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 6
 
10.2%
a 5
 
8.5%
r 4
 
6.8%
e 4
 
6.8%
i 4
 
6.8%
S 3
 
5.1%
t 3
 
5.1%
d 3
 
5.1%
I 3
 
5.1%
o 3
 
5.1%
Other values (16) 21
35.6%
Common
ValueCountFrequency (%)
12
38.7%
. 5
16.1%
( 4
 
12.9%
) 4
 
12.9%
2 3
 
9.7%
9 1
 
3.2%
3 1
 
3.2%
8 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
 
13.3%
n 6
 
6.7%
a 5
 
5.6%
. 5
 
5.6%
( 4
 
4.4%
r 4
 
4.4%
) 4
 
4.4%
e 4
 
4.4%
i 4
 
4.4%
S 3
 
3.3%
Other values (24) 39
43.3%

admissionsmethod_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:09.835505image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters22
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTalent Test
2nd rowTalent Test
ValueCountFrequency (%)
talent 2
50.0%
test 2
50.0%
2023-12-09T22:48:10.094005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 4
18.2%
e 4
18.2%
t 4
18.2%
a 2
9.1%
l 2
9.1%
n 2
9.1%
2
9.1%
s 2
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
72.7%
Uppercase Letter 4
 
18.2%
Space Separator 2
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
25.0%
t 4
25.0%
a 2
12.5%
l 2
12.5%
n 2
12.5%
s 2
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
90.9%
Common 2
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 4
20.0%
e 4
20.0%
t 4
20.0%
a 2
10.0%
l 2
10.0%
n 2
10.0%
s 2
10.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 4
18.2%
e 4
18.2%
t 4
18.2%
a 2
9.1%
l 2
9.1%
n 2
9.1%
2
9.1%
s 2
9.1%

geapps_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:10.251323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row324
2nd row194
ValueCountFrequency (%)
324 1
50.0%
194 1
50.0%
2023-12-09T22:48:10.520030image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2
33.3%
3 1
16.7%
2 1
16.7%
1 1
16.7%
9 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2
33.3%
3 1
16.7%
2 1
16.7%
1 1
16.7%
9 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2
33.3%
3 1
16.7%
2 1
16.7%
1 1
16.7%
9 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2
33.3%
3 1
16.7%
2 1
16.7%
1 1
16.7%
9 1
16.7%

swdapps_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:10.671024image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row18
2nd row15
ValueCountFrequency (%)
15 1
50.0%
18 1
50.0%
2023-12-09T22:48:10.931648image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
8 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
8 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
8 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
8 1
25.0%

geseats_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:11.078776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row27
2nd row26
ValueCountFrequency (%)
26 1
50.0%
27 1
50.0%
2023-12-09T22:48:11.330913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
50.0%
6 1
25.0%
7 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
50.0%
6 1
25.0%
7 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
50.0%
6 1
25.0%
7 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
50.0%
6 1
25.0%
7 1
25.0%

swdseats_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:11.432247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row6
ValueCountFrequency (%)
6 2
100.0%
2023-12-09T22:48:11.652858image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2
100.0%

geappsperseat_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:11.785494image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1.5
Mean length1.5
Min length1

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row12
2nd row7
ValueCountFrequency (%)
12 1
50.0%
7 1
50.0%
2023-12-09T22:48:12.035810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
7 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
7 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
7 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
7 1
33.3%

swdappsperseat_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:12.138674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
ValueCountFrequency (%)
3 2
100.0%
2023-12-09T22:48:12.347372image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
100.0%

gefilled_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:12.449076image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
ValueCountFrequency (%)
y 2
100.0%
2023-12-09T22:48:12.661882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 2
100.0%

swdfilled_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:48:12.762674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowN
ValueCountFrequency (%)
n 2
100.0%
2023-12-09T22:48:12.973161image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 2
100.0%

eligibility_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.1 KiB
2023-12-09T22:48:13.152835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length38
Mean length38
Min length31

Characters and Unicode

Total characters76
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to New York City residents
ValueCountFrequency (%)
open 2
14.3%
to 2
14.3%
residents 2
14.3%
students 1
7.1%
and 1
7.1%
of 1
7.1%
district 1
7.1%
21 1
7.1%
new 1
7.1%
york 1
7.1%
2023-12-09T22:48:13.467311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
15.8%
t 9
11.8%
e 8
10.5%
s 7
9.2%
n 6
 
7.9%
i 5
 
6.6%
r 4
 
5.3%
o 4
 
5.3%
d 4
 
5.3%
p 2
 
2.6%
Other values (14) 15
19.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 56
73.7%
Space Separator 12
 
15.8%
Uppercase Letter 6
 
7.9%
Decimal Number 2
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 9
16.1%
e 8
14.3%
s 7
12.5%
n 6
10.7%
i 5
8.9%
r 4
7.1%
o 4
7.1%
d 4
7.1%
p 2
 
3.6%
a 1
 
1.8%
Other values (6) 6
10.7%
Uppercase Letter
ValueCountFrequency (%)
O 2
33.3%
D 1
16.7%
N 1
16.7%
Y 1
16.7%
C 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 62
81.6%
Common 14
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 9
14.5%
e 8
12.9%
s 7
11.3%
n 6
9.7%
i 5
8.1%
r 4
 
6.5%
o 4
 
6.5%
d 4
 
6.5%
p 2
 
3.2%
O 2
 
3.2%
Other values (11) 11
17.7%
Common
ValueCountFrequency (%)
12
85.7%
2 1
 
7.1%
1 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
15.8%
t 9
11.8%
e 8
10.5%
s 7
9.2%
n 6
 
7.9%
i 5
 
6.6%
r 4
 
5.3%
o 4
 
5.3%
d 4
 
5.3%
p 2
 
2.6%
Other values (14) 15
19.7%

priority1_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:13.614649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228ST
ValueCountFrequency (%)
k228st 1
100.0%
2023-12-09T22:48:13.860351image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
S 1
16.7%
T 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
50.0%
Uppercase Letter 3
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
S 1
33.3%
T 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
50.0%
Latin 3
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 1
33.3%
S 1
33.3%
T 1
33.3%
Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
S 1
16.7%
T 1
16.7%

name_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:14.044132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters63
Distinct characters29
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Instrumental-Strings)
ValueCountFrequency (%)
david 1
12.5%
a 1
12.5%
boody 1
12.5%
i.s 1
12.5%
228 1
12.5%
magnet 1
12.5%
program 1
12.5%
instrumental-strings 1
12.5%
2023-12-09T22:48:14.348838image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
11.1%
n 4
 
6.3%
r 4
 
6.3%
a 4
 
6.3%
t 4
 
6.3%
g 3
 
4.8%
. 3
 
4.8%
o 3
 
4.8%
2 2
 
3.2%
I 2
 
3.2%
Other values (19) 27
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36
57.1%
Uppercase Letter 9
 
14.3%
Space Separator 7
 
11.1%
Other Punctuation 3
 
4.8%
Decimal Number 3
 
4.8%
Close Punctuation 2
 
3.2%
Open Punctuation 2
 
3.2%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 4
11.1%
r 4
11.1%
a 4
11.1%
t 4
11.1%
g 3
8.3%
o 3
8.3%
m 2
 
5.6%
s 2
 
5.6%
d 2
 
5.6%
i 2
 
5.6%
Other values (5) 6
16.7%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
S 2
22.2%
P 1
11.1%
D 1
11.1%
M 1
11.1%
B 1
11.1%
A 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45
71.4%
Common 18
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4
 
8.9%
r 4
 
8.9%
a 4
 
8.9%
t 4
 
8.9%
g 3
 
6.7%
o 3
 
6.7%
I 2
 
4.4%
S 2
 
4.4%
m 2
 
4.4%
s 2
 
4.4%
Other values (12) 15
33.3%
Common
ValueCountFrequency (%)
7
38.9%
. 3
16.7%
2 2
 
11.1%
) 2
 
11.1%
( 2
 
11.1%
8 1
 
5.6%
- 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
 
11.1%
n 4
 
6.3%
r 4
 
6.3%
a 4
 
6.3%
t 4
 
6.3%
g 3
 
4.8%
. 3
 
4.8%
o 3
 
4.8%
2 2
 
3.2%
I 2
 
3.2%
Other values (19) 27
42.9%

admissionsmethod_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:14.498799image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowTalent Test
ValueCountFrequency (%)
talent 1
50.0%
test 1
50.0%
2023-12-09T22:48:14.758295image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
72.7%
Uppercase Letter 2
 
18.2%
Space Separator 1
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
t 2
25.0%
a 1
12.5%
l 1
12.5%
n 1
12.5%
s 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
90.9%
Common 1
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
20.0%
e 2
20.0%
t 2
20.0%
a 1
10.0%
l 1
10.0%
n 1
10.0%
s 1
10.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

geapps_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:14.863907image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row57
ValueCountFrequency (%)
57 1
100.0%
2023-12-09T22:48:15.078318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1
50.0%
7 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1
50.0%
7 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1
50.0%
7 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1
50.0%
7 1
50.0%

swdapps_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:15.180309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:48:15.388774image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

geseats_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:15.490701image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row16
ValueCountFrequency (%)
16 1
100.0%
2023-12-09T22:48:15.708718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

swdseats_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:15.811043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2023-12-09T22:48:16.025139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

geappsperseat_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:16.128310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2023-12-09T22:48:16.346146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

swdappsperseat_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:16.447201image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1
ValueCountFrequency (%)
1 1
100.0%
2023-12-09T22:48:16.648814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
100.0%

gefilled_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:16.745065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowN
ValueCountFrequency (%)
n 1
100.0%
2023-12-09T22:48:16.957361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1
100.0%

swdfilled_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:17.058081image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowN
ValueCountFrequency (%)
n 1
100.0%
2023-12-09T22:48:17.277219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1
100.0%

eligibility_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:17.464913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters45
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 1
12.5%
to 1
12.5%
students 1
12.5%
and 1
12.5%
residents 1
12.5%
of 1
12.5%
district 1
12.5%
21 1
12.5%
2023-12-09T22:48:17.757558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
75.6%
Space Separator 7
 
15.6%
Decimal Number 2
 
4.4%
Uppercase Letter 2
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
d 3
8.8%
i 3
8.8%
o 2
 
5.9%
r 2
 
5.9%
f 1
 
2.9%
c 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
80.0%
Common 9
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
16.7%
s 5
13.9%
e 4
11.1%
n 4
11.1%
d 3
8.3%
i 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
f 1
 
2.8%
c 1
 
2.8%
Other values (5) 5
13.9%
Common
ValueCountFrequency (%)
7
77.8%
2 1
 
11.1%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

priority1_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:18.744753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228VO
ValueCountFrequency (%)
k228vo 1
100.0%
2023-12-09T22:48:19.007810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
V 1
16.7%
O 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
50.0%
Uppercase Letter 3
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
V 1
33.3%
O 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
50.0%
Latin 3
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 1
33.3%
V 1
33.3%
O 1
33.3%
Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
V 1
16.7%
O 1
16.7%

name_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:19.198749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length54
Median length54
Mean length54
Min length54

Characters and Unicode

Total characters54
Distinct characters30
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Vocal Music)
ValueCountFrequency (%)
david 1
11.1%
a 1
11.1%
boody 1
11.1%
i.s 1
11.1%
228 1
11.1%
magnet 1
11.1%
program 1
11.1%
vocal 1
11.1%
music 1
11.1%
2023-12-09T22:48:19.508405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
14.8%
o 4
 
7.4%
a 4
 
7.4%
. 3
 
5.6%
2 2
 
3.7%
g 2
 
3.7%
i 2
 
3.7%
d 2
 
3.7%
M 2
 
3.7%
c 2
 
3.7%
Other values (20) 23
42.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27
50.0%
Uppercase Letter 9
 
16.7%
Space Separator 8
 
14.8%
Other Punctuation 3
 
5.6%
Decimal Number 3
 
5.6%
Close Punctuation 2
 
3.7%
Open Punctuation 2
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
14.8%
a 4
14.8%
g 2
 
7.4%
i 2
 
7.4%
d 2
 
7.4%
c 2
 
7.4%
r 2
 
7.4%
m 1
 
3.7%
t 1
 
3.7%
l 1
 
3.7%
Other values (6) 6
22.2%
Uppercase Letter
ValueCountFrequency (%)
M 2
22.2%
D 1
11.1%
V 1
11.1%
P 1
11.1%
S 1
11.1%
I 1
11.1%
B 1
11.1%
A 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
66.7%
Common 18
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
 
11.1%
a 4
 
11.1%
g 2
 
5.6%
i 2
 
5.6%
d 2
 
5.6%
M 2
 
5.6%
c 2
 
5.6%
r 2
 
5.6%
D 1
 
2.8%
V 1
 
2.8%
Other values (14) 14
38.9%
Common
ValueCountFrequency (%)
8
44.4%
. 3
 
16.7%
2 2
 
11.1%
) 2
 
11.1%
( 2
 
11.1%
8 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
 
14.8%
o 4
 
7.4%
a 4
 
7.4%
. 3
 
5.6%
2 2
 
3.7%
g 2
 
3.7%
i 2
 
3.7%
d 2
 
3.7%
M 2
 
3.7%
c 2
 
3.7%
Other values (20) 23
42.6%

admissionsmethod_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:19.655974image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowTalent Test
ValueCountFrequency (%)
talent 1
50.0%
test 1
50.0%
2023-12-09T22:48:19.904705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
72.7%
Uppercase Letter 2
 
18.2%
Space Separator 1
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
t 2
25.0%
a 1
12.5%
l 1
12.5%
n 1
12.5%
s 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
90.9%
Common 1
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
20.0%
e 2
20.0%
t 2
20.0%
a 1
10.0%
l 1
10.0%
n 1
10.0%
s 1
10.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

geapps_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:20.006558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row78
ValueCountFrequency (%)
78 1
100.0%
2023-12-09T22:48:20.217988image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1
50.0%
8 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1
50.0%
8 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1
50.0%
8 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1
50.0%
8 1
50.0%

swdapps_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:20.323694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row11
ValueCountFrequency (%)
11 1
100.0%
2023-12-09T22:48:20.538589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
100.0%

geseats_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:20.645263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row8
ValueCountFrequency (%)
8 1
100.0%
2023-12-09T22:48:20.862864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1
100.0%

swdseats_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:20.964847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:48:21.184136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

geappsperseat_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:21.287136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row10
ValueCountFrequency (%)
10 1
100.0%
2023-12-09T22:48:21.506078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
0 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
0 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
0 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
0 1
50.0%

swdappsperseat_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:21.609022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row6
ValueCountFrequency (%)
6 1
100.0%
2023-12-09T22:48:21.824262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
100.0%

gefilled_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:21.928782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowY
ValueCountFrequency (%)
y 1
100.0%
2023-12-09T22:48:22.139443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
100.0%

swdfilled_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:22.240966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowN
ValueCountFrequency (%)
n 1
100.0%
2023-12-09T22:48:22.447939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1
100.0%

eligibility_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:22.628996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters45
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 1
12.5%
to 1
12.5%
students 1
12.5%
and 1
12.5%
residents 1
12.5%
of 1
12.5%
district 1
12.5%
21 1
12.5%
2023-12-09T22:48:22.925251image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
75.6%
Space Separator 7
 
15.6%
Decimal Number 2
 
4.4%
Uppercase Letter 2
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
d 3
8.8%
i 3
8.8%
o 2
 
5.9%
r 2
 
5.9%
f 1
 
2.9%
c 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
80.0%
Common 9
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
16.7%
s 5
13.9%
e 4
11.1%
n 4
11.1%
d 3
8.3%
i 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
f 1
 
2.8%
c 1
 
2.8%
Other values (5) 5
13.9%
Common
ValueCountFrequency (%)
7
77.8%
2 1
 
11.1%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

priority1_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:23.072612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228WI
ValueCountFrequency (%)
k228wi 1
100.0%
2023-12-09T22:48:23.325623image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
W 1
16.7%
I 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
50.0%
Uppercase Letter 3
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
W 1
33.3%
I 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
50.0%
Latin 3
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 1
33.3%
W 1
33.3%
I 1
33.3%
Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
W 1
16.7%
I 1
16.7%

name_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:23.513255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters63
Distinct characters30
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Instrumental - Winds)
ValueCountFrequency (%)
david 1
10.0%
a 1
10.0%
boody 1
10.0%
i.s 1
10.0%
228 1
10.0%
magnet 1
10.0%
program 1
10.0%
instrumental 1
10.0%
1
10.0%
winds 1
10.0%
2023-12-09T22:48:23.819242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
14.3%
n 4
 
6.3%
a 4
 
6.3%
t 3
 
4.8%
d 3
 
4.8%
. 3
 
4.8%
r 3
 
4.8%
o 3
 
4.8%
m 2
 
3.2%
e 2
 
3.2%
Other values (20) 27
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
54.0%
Space Separator 9
 
14.3%
Uppercase Letter 9
 
14.3%
Other Punctuation 3
 
4.8%
Decimal Number 3
 
4.8%
Close Punctuation 2
 
3.2%
Open Punctuation 2
 
3.2%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 4
11.8%
a 4
11.8%
t 3
8.8%
d 3
8.8%
r 3
8.8%
o 3
8.8%
m 2
 
5.9%
e 2
 
5.9%
g 2
 
5.9%
s 2
 
5.9%
Other values (5) 6
17.6%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
P 1
11.1%
D 1
11.1%
M 1
11.1%
S 1
11.1%
B 1
11.1%
A 1
11.1%
W 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43
68.3%
Common 20
31.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4
 
9.3%
a 4
 
9.3%
t 3
 
7.0%
d 3
 
7.0%
r 3
 
7.0%
o 3
 
7.0%
m 2
 
4.7%
e 2
 
4.7%
g 2
 
4.7%
I 2
 
4.7%
Other values (13) 15
34.9%
Common
ValueCountFrequency (%)
9
45.0%
. 3
 
15.0%
) 2
 
10.0%
2 2
 
10.0%
( 2
 
10.0%
- 1
 
5.0%
8 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
 
14.3%
n 4
 
6.3%
a 4
 
6.3%
t 3
 
4.8%
d 3
 
4.8%
. 3
 
4.8%
r 3
 
4.8%
o 3
 
4.8%
m 2
 
3.2%
e 2
 
3.2%
Other values (20) 27
42.9%

admissionsmethod_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:23.970428image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowTalent Test
ValueCountFrequency (%)
talent 1
50.0%
test 1
50.0%
2023-12-09T22:48:24.238023image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
72.7%
Uppercase Letter 2
 
18.2%
Space Separator 1
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
t 2
25.0%
a 1
12.5%
l 1
12.5%
n 1
12.5%
s 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
90.9%
Common 1
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
20.0%
e 2
20.0%
t 2
20.0%
a 1
10.0%
l 1
10.0%
n 1
10.0%
s 1
10.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

geapps_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:24.341114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row64
ValueCountFrequency (%)
64 1
100.0%
2023-12-09T22:48:24.550343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
50.0%
4 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
50.0%
4 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
50.0%
4 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
50.0%
4 1
50.0%

swdapps_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:24.650898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row6
ValueCountFrequency (%)
6 1
100.0%
2023-12-09T22:48:24.861560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
100.0%

geseats_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:24.964541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row16
ValueCountFrequency (%)
16 1
100.0%
2023-12-09T22:48:25.175576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

swdseats_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:25.275730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2023-12-09T22:48:25.485057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

geappsperseat_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:25.587176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2023-12-09T22:48:25.792554image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

swdappsperseat_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:25.891466image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:48:26.098600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

gefilled_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:26.198775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowN
ValueCountFrequency (%)
n 1
100.0%
2023-12-09T22:48:26.408140image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1
100.0%

swdfilled_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:26.507035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowN
ValueCountFrequency (%)
n 1
100.0%
2023-12-09T22:48:26.713828image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1
100.0%

eligibility_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:26.893769image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters45
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 1
12.5%
to 1
12.5%
students 1
12.5%
and 1
12.5%
residents 1
12.5%
of 1
12.5%
district 1
12.5%
21 1
12.5%
2023-12-09T22:48:27.199689image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
75.6%
Space Separator 7
 
15.6%
Decimal Number 2
 
4.4%
Uppercase Letter 2
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
d 3
8.8%
i 3
8.8%
o 2
 
5.9%
r 2
 
5.9%
f 1
 
2.9%
c 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
80.0%
Common 9
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
16.7%
s 5
13.9%
e 4
11.1%
n 4
11.1%
d 3
8.3%
i 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
f 1
 
2.8%
c 1
 
2.8%
Other values (5) 5
13.9%
Common
ValueCountFrequency (%)
7
77.8%
2 1
 
11.1%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

priority1_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:27.344705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228Z
ValueCountFrequency (%)
k228z 1
100.0%
2023-12-09T22:48:27.595226image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
40.0%
K 1
20.0%
8 1
20.0%
Z 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
60.0%
Uppercase Letter 2
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
Z 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3
60.0%
Latin 2
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Latin
ValueCountFrequency (%)
K 1
50.0%
Z 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
40.0%
K 1
20.0%
8 1
20.0%
Z 1
20.0%

name_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:27.774577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters39
Distinct characters24
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Zoned Program
ValueCountFrequency (%)
david 1
14.3%
a 1
14.3%
boody 1
14.3%
i.s 1
14.3%
228 1
14.3%
zoned 1
14.3%
program 1
14.3%
2023-12-09T22:48:28.071448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
15.4%
o 4
 
10.3%
d 3
 
7.7%
. 3
 
7.7%
r 2
 
5.1%
a 2
 
5.1%
2 2
 
5.1%
D 1
 
2.6%
8 1
 
2.6%
g 1
 
2.6%
Other values (14) 14
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
46.2%
Uppercase Letter 7
 
17.9%
Space Separator 6
 
15.4%
Other Punctuation 3
 
7.7%
Decimal Number 3
 
7.7%
Close Punctuation 1
 
2.6%
Open Punctuation 1
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
22.2%
d 3
16.7%
r 2
11.1%
a 2
11.1%
g 1
 
5.6%
e 1
 
5.6%
n 1
 
5.6%
y 1
 
5.6%
i 1
 
5.6%
v 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
D 1
14.3%
P 1
14.3%
Z 1
14.3%
I 1
14.3%
S 1
14.3%
B 1
14.3%
A 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25
64.1%
Common 14
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
16.0%
d 3
 
12.0%
r 2
 
8.0%
a 2
 
8.0%
D 1
 
4.0%
g 1
 
4.0%
P 1
 
4.0%
e 1
 
4.0%
n 1
 
4.0%
Z 1
 
4.0%
Other values (8) 8
32.0%
Common
ValueCountFrequency (%)
6
42.9%
. 3
21.4%
2 2
 
14.3%
8 1
 
7.1%
) 1
 
7.1%
( 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
15.4%
o 4
 
10.3%
d 3
 
7.7%
. 3
 
7.7%
r 2
 
5.1%
a 2
 
5.1%
2 2
 
5.1%
D 1
 
2.6%
8 1
 
2.6%
g 1
 
2.6%
Other values (14) 14
35.9%

admissionsmethod_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:28.212399image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowZoned
ValueCountFrequency (%)
zoned 1
100.0%
2023-12-09T22:48:28.459146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4
80.0%
Uppercase Letter 1
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
n 1
25.0%
e 1
25.0%
d 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
Z 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

geapps_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:28.570931image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row217
ValueCountFrequency (%)
217 1
100.0%
2023-12-09T22:48:28.792643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
33.3%
1 1
33.3%
7 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
33.3%
1 1
33.3%
7 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
33.3%
1 1
33.3%
7 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
33.3%
1 1
33.3%
7 1
33.3%

swdapps_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:28.895260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row53
ValueCountFrequency (%)
53 1
100.0%
2023-12-09T22:48:29.106954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1
50.0%
3 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1
50.0%
3 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1
50.0%
3 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1
50.0%
3 1
50.0%

geseats_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:29.220639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row114
ValueCountFrequency (%)
114 1
100.0%
2023-12-09T22:48:29.441556image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
66.7%
4 1
33.3%

swdseats_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:29.541733image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row27
ValueCountFrequency (%)
27 1
100.0%
2023-12-09T22:48:29.751755image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
50.0%
7 1
50.0%

geappsperseat_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:29.852037image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:48:30.060961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

swdappsperseat_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:30.161065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:48:30.371598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

gefilled_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:30.472843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowY
ValueCountFrequency (%)
y 1
100.0%
2023-12-09T22:48:30.682822image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
100.0%

swdfilled_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:30.783377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowY
ValueCountFrequency (%)
y 1
100.0%
2023-12-09T22:48:31.002087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 1
100.0%

eligibility_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:48:31.184490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters37
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students residing in the zone
ValueCountFrequency (%)
open 1
14.3%
to 1
14.3%
students 1
14.3%
residing 1
14.3%
in 1
14.3%
the 1
14.3%
zone 1
14.3%
2023-12-09T22:48:31.488459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
16.2%
e 5
13.5%
n 5
13.5%
t 4
10.8%
s 3
8.1%
i 3
8.1%
o 2
 
5.4%
d 2
 
5.4%
O 1
 
2.7%
p 1
 
2.7%
Other values (5) 5
13.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30
81.1%
Space Separator 6
 
16.2%
Uppercase Letter 1
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5
16.7%
n 5
16.7%
t 4
13.3%
s 3
10.0%
i 3
10.0%
o 2
 
6.7%
d 2
 
6.7%
p 1
 
3.3%
u 1
 
3.3%
r 1
 
3.3%
Other values (3) 3
10.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31
83.8%
Common 6
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5
16.1%
n 5
16.1%
t 4
12.9%
s 3
9.7%
i 3
9.7%
o 2
 
6.5%
d 2
 
6.5%
O 1
 
3.2%
p 1
 
3.2%
u 1
 
3.2%
Other values (4) 4
12.9%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
16.2%
e 5
13.5%
n 5
13.5%
t 4
10.8%
s 3
8.1%
i 3
8.1%
o 2
 
5.4%
d 2
 
5.4%
O 1
 
2.7%
p 1
 
2.7%
Other values (5) 5
13.5%

priority1_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

coursepassrate
Text

MISSING 

Distinct42
Distinct (%)9.0%
Missing6
Missing (%)1.3%
Memory size27.4 KiB
2023-12-09T22:48:31.733301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length17
Median length2
Mean length2.213675214
Min length2

Characters and Unicode

Total characters1036
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.6%

Sample

1st row95
2nd row90
3rd row98
4th row87
5th row83
ValueCountFrequency (%)
99 51
 
10.9%
100 40
 
8.5%
98 39
 
8.3%
97 32
 
6.8%
95 30
 
6.4%
94 29
 
6.2%
96 28
 
6.0%
93 28
 
6.0%
92 22
 
4.7%
91 22
 
4.7%
Other values (32) 147
31.4%
2023-12-09T22:48:32.110242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 412
39.8%
8 153
 
14.8%
0 120
 
11.6%
7 70
 
6.8%
1 67
 
6.5%
6 52
 
5.0%
5 47
 
4.5%
4 43
 
4.2%
3 35
 
3.4%
2 33
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1032
99.6%
Other Punctuation 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 412
39.9%
8 153
 
14.8%
0 120
 
11.6%
7 70
 
6.8%
1 67
 
6.5%
6 52
 
5.0%
5 47
 
4.6%
4 43
 
4.2%
3 35
 
3.4%
2 33
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1036
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 412
39.8%
8 153
 
14.8%
0 120
 
11.6%
7 70
 
6.8%
1 67
 
6.5%
6 52
 
5.0%
5 47
 
4.5%
4 43
 
4.2%
3 35
 
3.4%
2 33
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 412
39.8%
8 153
 
14.8%
0 120
 
11.6%
7 70
 
6.8%
1 67
 
6.5%
6 52
 
5.0%
5 47
 
4.5%
4 43
 
4.2%
3 35
 
3.4%
2 33
 
3.2%

elaprof
Text

MISSING 

Distinct88
Distinct (%)18.8%
Missing6
Missing (%)1.3%
Memory size27.3 KiB
2023-12-09T22:48:32.450219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.993589744
Min length1

Characters and Unicode

Total characters933
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)3.2%

Sample

1st row19
2nd row27
3rd row76
4th row25
5th row28
ValueCountFrequency (%)
28 21
 
4.5%
24 20
 
4.3%
34 16
 
3.4%
27 16
 
3.4%
31 14
 
3.0%
35 12
 
2.6%
26 11
 
2.4%
38 11
 
2.4%
30 11
 
2.4%
17 10
 
2.1%
Other values (78) 326
69.7%
2023-12-09T22:48:32.905757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 149
16.0%
3 137
14.7%
4 124
13.3%
6 101
10.8%
5 95
10.2%
1 89
9.5%
7 74
7.9%
8 65
7.0%
9 51
 
5.5%
0 48
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 933
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 149
16.0%
3 137
14.7%
4 124
13.3%
6 101
10.8%
5 95
10.2%
1 89
9.5%
7 74
7.9%
8 65
7.0%
9 51
 
5.5%
0 48
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 933
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 149
16.0%
3 137
14.7%
4 124
13.3%
6 101
10.8%
5 95
10.2%
1 89
9.5%
7 74
7.9%
8 65
7.0%
9 51
 
5.5%
0 48
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 149
16.0%
3 137
14.7%
4 124
13.3%
6 101
10.8%
5 95
10.2%
1 89
9.5%
7 74
7.9%
8 65
7.0%
9 51
 
5.5%
0 48
 
5.1%

mathprof
Text

MISSING 

Distinct93
Distinct (%)19.9%
Missing6
Missing (%)1.3%
Memory size27.3 KiB
2023-12-09T22:48:33.245767image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.957264957
Min length1

Characters and Unicode

Total characters916
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)2.8%

Sample

1st row14
2nd row21
3rd row82
4th row21
5th row13
ValueCountFrequency (%)
14 14
 
3.0%
13 14
 
3.0%
28 13
 
2.8%
56 13
 
2.8%
15 12
 
2.6%
20 12
 
2.6%
22 11
 
2.4%
16 11
 
2.4%
11 11
 
2.4%
24 10
 
2.1%
Other values (83) 347
74.1%
2023-12-09T22:48:33.713700image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 144
15.7%
2 129
14.1%
5 107
11.7%
3 106
11.6%
4 104
11.4%
6 88
9.6%
7 66
7.2%
8 60
6.6%
0 56
 
6.1%
9 56
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 916
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 144
15.7%
2 129
14.1%
5 107
11.7%
3 106
11.6%
4 104
11.4%
6 88
9.6%
7 66
7.2%
8 60
6.6%
0 56
 
6.1%
9 56
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common 916
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 144
15.7%
2 129
14.1%
5 107
11.7%
3 106
11.6%
4 104
11.4%
6 88
9.6%
7 66
7.2%
8 60
6.6%
0 56
 
6.1%
9 56
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 916
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 144
15.7%
2 129
14.1%
5 107
11.7%
3 106
11.6%
4 104
11.4%
6 88
9.6%
7 66
7.2%
8 60
6.6%
0 56
 
6.1%
9 56
 
6.1%

tophs1
Text

MISSING 

Distinct237
Distinct (%)51.4%
Missing13
Missing (%)2.7%
Memory size41.9 KiB
2023-12-09T22:48:34.059449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length88
Median length61
Mean length34.87418655
Min length11

Characters and Unicode

Total characters16077
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)31.2%

Sample

1st rowHudson High School of Learning Technologies
2nd rowOrchard Collegiate Academy
3rd rowBrooklyn Technical High School
4th rowUrban Assembly Academy of Government and Law, The
5th rowLower Manhattan Arts Academy
ValueCountFrequency (%)
school 373
 
15.5%
high 302
 
12.5%
for 92
 
3.8%
and 81
 
3.4%
academy 80
 
3.3%
of 49
 
2.0%
the 48
 
2.0%
college 35
 
1.5%
technology 28
 
1.2%
arts 27
 
1.1%
Other values (341) 1293
53.7%
2023-12-09T22:48:34.610517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1947
 
12.1%
o 1545
 
9.6%
e 1046
 
6.5%
h 950
 
5.9%
a 909
 
5.7%
i 895
 
5.6%
l 846
 
5.3%
n 831
 
5.2%
r 829
 
5.2%
c 753
 
4.7%
Other values (58) 5526
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11783
73.3%
Uppercase Letter 2190
 
13.6%
Space Separator 1947
 
12.1%
Other Punctuation 122
 
0.8%
Decimal Number 17
 
0.1%
Open Punctuation 6
 
< 0.1%
Dash Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1545
13.1%
e 1046
 
8.9%
h 950
 
8.1%
a 909
 
7.7%
i 895
 
7.6%
l 846
 
7.2%
n 831
 
7.1%
r 829
 
7.0%
c 753
 
6.4%
t 530
 
4.5%
Other values (16) 2649
22.5%
Uppercase Letter
ValueCountFrequency (%)
S 497
22.7%
H 391
17.9%
A 184
 
8.4%
C 169
 
7.7%
T 115
 
5.3%
B 108
 
4.9%
M 99
 
4.5%
E 88
 
4.0%
L 79
 
3.6%
P 74
 
3.4%
Other values (15) 386
17.6%
Decimal Number
ValueCountFrequency (%)
2 5
29.4%
3 4
23.5%
7 2
 
11.8%
1 2
 
11.8%
4 2
 
11.8%
6 1
 
5.9%
8 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 50
41.0%
, 36
29.5%
: 17
 
13.9%
& 10
 
8.2%
' 6
 
4.9%
/ 3
 
2.5%
Space Separator
ValueCountFrequency (%)
1947
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13973
86.9%
Common 2104
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1545
 
11.1%
e 1046
 
7.5%
h 950
 
6.8%
a 909
 
6.5%
i 895
 
6.4%
l 846
 
6.1%
n 831
 
5.9%
r 829
 
5.9%
c 753
 
5.4%
t 530
 
3.8%
Other values (41) 4839
34.6%
Common
ValueCountFrequency (%)
1947
92.5%
. 50
 
2.4%
, 36
 
1.7%
: 17
 
0.8%
& 10
 
0.5%
( 6
 
0.3%
- 6
 
0.3%
) 6
 
0.3%
' 6
 
0.3%
2 5
 
0.2%
Other values (7) 15
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1947
 
12.1%
o 1545
 
9.6%
e 1046
 
6.5%
h 950
 
5.9%
a 909
 
5.7%
i 895
 
5.6%
l 846
 
5.3%
n 831
 
5.2%
r 829
 
5.2%
c 753
 
4.7%
Other values (58) 5526
34.4%

tophs2
Text

MISSING 

Distinct182
Distinct (%)49.5%
Missing106
Missing (%)22.4%
Memory size36.9 KiB
2023-12-09T22:48:35.026836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length60
Mean length36.12228261
Min length13

Characters and Unicode

Total characters13293
Distinct characters64
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)29.1%

Sample

1st rowOrchard Collegiate Academy
2nd rowNew Explorations into Science, Technology and Math High School
3rd rowMillennium High School
4th rowLower Manhattan Arts Academy
5th rowManhattan Early College School for Advertising
ValueCountFrequency (%)
school 323
 
15.8%
high 284
 
13.9%
and 82
 
4.0%
for 69
 
3.4%
of 49
 
2.4%
academy 48
 
2.4%
arts 39
 
1.9%
the 39
 
1.9%
technical 29
 
1.4%
bronx 27
 
1.3%
Other values (283) 1053
51.6%
2023-12-09T22:48:35.639147image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1674
 
12.6%
o 1284
 
9.7%
h 843
 
6.3%
e 806
 
6.1%
i 789
 
5.9%
a 721
 
5.4%
l 714
 
5.4%
c 666
 
5.0%
r 655
 
4.9%
n 629
 
4.7%
Other values (54) 4512
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9610
72.3%
Uppercase Letter 1867
 
14.0%
Space Separator 1674
 
12.6%
Other Punctuation 124
 
0.9%
Decimal Number 6
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1284
13.4%
h 843
8.8%
e 806
 
8.4%
i 789
 
8.2%
a 721
 
7.5%
l 714
 
7.4%
c 666
 
6.9%
r 655
 
6.8%
n 629
 
6.5%
t 408
 
4.2%
Other values (16) 2095
21.8%
Uppercase Letter
ValueCountFrequency (%)
S 411
22.0%
H 354
19.0%
C 152
 
8.1%
A 149
 
8.0%
T 107
 
5.7%
B 100
 
5.4%
M 94
 
5.0%
E 73
 
3.9%
L 63
 
3.4%
P 49
 
2.6%
Other values (14) 315
16.9%
Other Punctuation
ValueCountFrequency (%)
. 75
60.5%
& 20
 
16.1%
, 19
 
15.3%
: 7
 
5.6%
/ 2
 
1.6%
' 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
4 1
 
16.7%
5 1
 
16.7%
7 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1674
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11477
86.3%
Common 1816
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1284
 
11.2%
h 843
 
7.3%
e 806
 
7.0%
i 789
 
6.9%
a 721
 
6.3%
l 714
 
6.2%
c 666
 
5.8%
r 655
 
5.7%
n 629
 
5.5%
S 411
 
3.6%
Other values (40) 3959
34.5%
Common
ValueCountFrequency (%)
1674
92.2%
. 75
 
4.1%
& 20
 
1.1%
, 19
 
1.0%
: 7
 
0.4%
( 5
 
0.3%
) 5
 
0.3%
1 3
 
0.2%
- 2
 
0.1%
/ 2
 
0.1%
Other values (4) 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13293
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1674
 
12.6%
o 1284
 
9.7%
h 843
 
6.3%
e 806
 
6.1%
i 789
 
5.9%
a 721
 
5.4%
l 714
 
5.4%
c 666
 
5.0%
r 655
 
4.9%
n 629
 
4.7%
Other values (54) 4512
33.9%

tophs3
Text

MISSING 

Distinct113
Distinct (%)52.8%
Missing260
Missing (%)54.9%
Memory size27.5 KiB
2023-12-09T22:48:35.944885image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length69
Median length54
Mean length35.1635514
Min length18

Characters and Unicode

Total characters7525
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)29.4%

Sample

1st rowStuyvesant High School
2nd rowEssex Street Academy
3rd rowBrooklyn Technical High School
4th rowEleanor Roosevelt High School
5th rowThe Bronx High School of Science
ValueCountFrequency (%)
school 193
 
16.8%
high 173
 
15.1%
for 45
 
3.9%
and 38
 
3.3%
of 25
 
2.2%
academy 25
 
2.2%
technical 24
 
2.1%
the 23
 
2.0%
bronx 22
 
1.9%
science 20
 
1.7%
Other values (209) 559
48.7%
2023-12-09T22:48:36.434252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
933
 
12.4%
o 739
 
9.8%
h 507
 
6.7%
i 460
 
6.1%
e 456
 
6.1%
l 412
 
5.5%
c 409
 
5.4%
a 397
 
5.3%
n 383
 
5.1%
r 359
 
4.8%
Other values (46) 2470
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5486
72.9%
Uppercase Letter 1050
 
14.0%
Space Separator 933
 
12.4%
Other Punctuation 54
 
0.7%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 739
13.5%
h 507
9.2%
i 460
8.4%
e 456
8.3%
l 412
 
7.5%
c 409
 
7.5%
a 397
 
7.2%
n 383
 
7.0%
r 359
 
6.5%
g 237
 
4.3%
Other values (16) 1127
20.5%
Uppercase Letter
ValueCountFrequency (%)
S 258
24.6%
H 192
18.3%
C 81
 
7.7%
A 72
 
6.9%
B 69
 
6.6%
T 65
 
6.2%
M 46
 
4.4%
R 36
 
3.4%
E 34
 
3.2%
L 27
 
2.6%
Other values (14) 170
16.2%
Other Punctuation
ValueCountFrequency (%)
. 36
66.7%
& 7
 
13.0%
, 7
 
13.0%
: 4
 
7.4%
Space Separator
ValueCountFrequency (%)
933
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6536
86.9%
Common 989
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 739
 
11.3%
h 507
 
7.8%
i 460
 
7.0%
e 456
 
7.0%
l 412
 
6.3%
c 409
 
6.3%
a 397
 
6.1%
n 383
 
5.9%
r 359
 
5.5%
S 258
 
3.9%
Other values (40) 2156
33.0%
Common
ValueCountFrequency (%)
933
94.3%
. 36
 
3.6%
& 7
 
0.7%
, 7
 
0.7%
: 4
 
0.4%
- 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
933
 
12.4%
o 739
 
9.8%
h 507
 
6.7%
i 460
 
6.1%
e 456
 
6.1%
l 412
 
5.5%
c 409
 
5.4%
a 397
 
5.3%
n 383
 
5.1%
r 359
 
4.8%
Other values (46) 2470
32.8%

surveysafety
Text

MISSING 

Distinct41
Distinct (%)8.8%
Missing6
Missing (%)1.3%
Memory size27.3 KiB
2023-12-09T22:48:36.696153image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length17
Median length2
Mean length2.066239316
Min length2

Characters and Unicode

Total characters967
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)1.5%

Sample

1st row75
2nd row81
3rd row86
4th row100
5th row82
ValueCountFrequency (%)
85 31
 
6.6%
87 29
 
6.2%
88 29
 
6.2%
86 24
 
5.1%
78 23
 
4.9%
84 21
 
4.5%
90 21
 
4.5%
81 19
 
4.1%
80 18
 
3.8%
89 17
 
3.6%
Other values (31) 236
50.4%
2023-12-09T22:48:37.077172image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 275
28.4%
9 174
18.0%
7 168
17.4%
6 80
 
8.3%
5 54
 
5.6%
0 49
 
5.1%
1 44
 
4.6%
2 42
 
4.3%
4 41
 
4.2%
3 38
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 965
99.8%
Other Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 275
28.5%
9 174
18.0%
7 168
17.4%
6 80
 
8.3%
5 54
 
5.6%
0 49
 
5.1%
1 44
 
4.6%
2 42
 
4.4%
4 41
 
4.2%
3 38
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 967
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 275
28.4%
9 174
18.0%
7 168
17.4%
6 80
 
8.3%
5 54
 
5.6%
0 49
 
5.1%
1 44
 
4.6%
2 42
 
4.3%
4 41
 
4.2%
3 38
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 967
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 275
28.4%
9 174
18.0%
7 168
17.4%
6 80
 
8.3%
5 54
 
5.6%
0 49
 
5.1%
1 44
 
4.6%
2 42
 
4.3%
4 41
 
4.2%
3 38
 
3.9%

totalstudents
Text

Distinct390
Distinct (%)82.8%
Missing3
Missing (%)0.6%
Memory size27.9 KiB
2023-12-09T22:48:37.643020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.16985138
Min length2

Characters and Unicode

Total characters1493
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique318 ?
Unique (%)67.5%

Sample

1st row296
2nd row372
3rd row707
4th row398
5th row218
ValueCountFrequency (%)
523 4
 
0.8%
329 3
 
0.6%
1000 3
 
0.6%
363 3
 
0.6%
461 3
 
0.6%
557 3
 
0.6%
525 3
 
0.6%
559 3
 
0.6%
371 2
 
0.4%
668 2
 
0.4%
Other values (380) 442
93.8%
2023-12-09T22:48:38.347490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 211
14.1%
3 182
12.2%
2 176
11.8%
5 169
11.3%
4 165
11.1%
6 144
9.6%
8 126
8.4%
7 123
8.2%
0 105
7.0%
9 92
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1493
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 211
14.1%
3 182
12.2%
2 176
11.8%
5 169
11.3%
4 165
11.1%
6 144
9.6%
8 126
8.4%
7 123
8.2%
0 105
7.0%
9 92
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1493
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 211
14.1%
3 182
12.2%
2 176
11.8%
5 169
11.3%
4 165
11.1%
6 144
9.6%
8 126
8.4%
7 123
8.2%
0 105
7.0%
9 92
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 211
14.1%
3 182
12.2%
2 176
11.8%
5 169
11.3%
4 165
11.1%
6 144
9.6%
8 126
8.4%
7 123
8.2%
0 105
7.0%
9 92
6.2%

gradespan
Text

Distinct13
Distinct (%)2.8%
Missing2
Missing (%)0.4%
Memory size28.0 KiB
2023-12-09T22:48:38.518129image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.389830508
Min length3

Characters and Unicode

Total characters1600
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.3%

Sample

1st rowPK-8
2nd rowPK-8
3rd rowPK-8
4th rowPK-8
5th row6-8
ValueCountFrequency (%)
6-8 256
54.1%
pk-8 93
 
19.7%
6-12 75
 
15.9%
k-8 36
 
7.6%
5-8 3
 
0.6%
k-12 2
 
0.4%
pk-12 2
 
0.4%
3-8 1
 
0.2%
7-12 1
 
0.2%
6-9 1
 
0.2%
Other values (3) 3
 
0.6%
2023-12-09T22:48:38.817459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 472
29.5%
8 390
24.4%
6 333
20.8%
K 134
 
8.4%
P 96
 
6.0%
1 80
 
5.0%
2 80
 
5.0%
5 3
 
0.2%
a 1
 
0.1%
: 1
 
0.1%
Other values (10) 10
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 890
55.6%
Dash Punctuation 472
29.5%
Uppercase Letter 231
 
14.4%
Lowercase Letter 5
 
0.3%
Other Punctuation 1
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 390
43.8%
6 333
37.4%
1 80
 
9.0%
2 80
 
9.0%
5 3
 
0.3%
9 1
 
0.1%
4 1
 
0.1%
7 1
 
0.1%
3 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
20.0%
s 1
20.0%
e 1
20.0%
d 1
20.0%
r 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
K 134
58.0%
P 96
41.6%
G 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 472
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1364
85.2%
Latin 236
 
14.8%

Most frequent character per script

Common
ValueCountFrequency (%)
- 472
34.6%
8 390
28.6%
6 333
24.4%
1 80
 
5.9%
2 80
 
5.9%
5 3
 
0.2%
: 1
 
0.1%
9 1
 
0.1%
4 1
 
0.1%
7 1
 
0.1%
Other values (2) 2
 
0.1%
Latin
ValueCountFrequency (%)
K 134
56.8%
P 96
40.7%
a 1
 
0.4%
s 1
 
0.4%
e 1
 
0.4%
d 1
 
0.4%
r 1
 
0.4%
G 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 472
29.5%
8 390
24.4%
6 333
20.8%
K 134
 
8.4%
P 96
 
6.0%
1 80
 
5.0%
2 80
 
5.0%
5 3
 
0.2%
a 1
 
0.1%
: 1
 
0.1%
Other values (10) 10
 
0.6%

diversityinadmissions
Text

MISSING 

Distinct6
Distinct (%)18.8%
Missing442
Missing (%)93.2%
Memory size20.6 KiB
2023-12-09T22:48:39.071762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length345
Median length165
Mean length156.1875
Min length116

Characters and Unicode

Total characters4998
Distinct characters49
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.4%

Sample

1st rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 62 percent of the seats
2nd rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 17 percent of seats
3rd rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 17 percent of seats
4th rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 17 percent of seats
5th rowThis program prioritizes 25% of seats for students who qualify for the federal free or reduced price lunch program (FRL) and who are lower-performing.
ValueCountFrequency (%)
for 53
 
6.7%
students 37
 
4.6%
of 34
 
4.3%
seats 34
 
4.3%
this 32
 
4.0%
and 31
 
3.9%
who 30
 
3.8%
program 30
 
3.8%
lunch 20
 
2.5%
free 20
 
2.5%
Other values (59) 475
59.7%
2023-12-09T22:48:39.457933image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
764
15.3%
e 390
 
7.8%
r 387
 
7.7%
o 369
 
7.4%
s 305
 
6.1%
i 261
 
5.2%
a 246
 
4.9%
t 227
 
4.5%
n 213
 
4.3%
h 175
 
3.5%
Other values (39) 1661
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3751
75.1%
Space Separator 764
 
15.3%
Uppercase Letter 203
 
4.1%
Decimal Number 100
 
2.0%
Other Punctuation 92
 
1.8%
Open Punctuation 31
 
0.6%
Close Punctuation 31
 
0.6%
Dash Punctuation 26
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 390
 
10.4%
r 387
 
10.3%
o 369
 
9.8%
s 305
 
8.1%
i 261
 
7.0%
a 246
 
6.6%
t 227
 
6.1%
n 213
 
5.7%
h 175
 
4.7%
f 160
 
4.3%
Other values (13) 1018
27.1%
Decimal Number
ValueCountFrequency (%)
5 34
34.0%
2 32
32.0%
1 11
 
11.0%
7 8
 
8.0%
6 4
 
4.0%
9 4
 
4.0%
3 3
 
3.0%
4 2
 
2.0%
0 1
 
1.0%
8 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
L 69
34.0%
F 25
 
12.3%
R 25
 
12.3%
S 24
 
11.8%
E 22
 
10.8%
T 21
 
10.3%
P 15
 
7.4%
D 2
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 33
35.9%
% 29
31.5%
. 28
30.4%
: 2
 
2.2%
Space Separator
ValueCountFrequency (%)
764
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3954
79.1%
Common 1044
 
20.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 390
 
9.9%
r 387
 
9.8%
o 369
 
9.3%
s 305
 
7.7%
i 261
 
6.6%
a 246
 
6.2%
t 227
 
5.7%
n 213
 
5.4%
h 175
 
4.4%
f 160
 
4.0%
Other values (21) 1221
30.9%
Common
ValueCountFrequency (%)
764
73.2%
5 34
 
3.3%
, 33
 
3.2%
2 32
 
3.1%
( 31
 
3.0%
) 31
 
3.0%
% 29
 
2.8%
. 28
 
2.7%
- 26
 
2.5%
1 11
 
1.1%
Other values (8) 25
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
764
15.3%
e 390
 
7.8%
r 387
 
7.7%
o 369
 
7.4%
s 305
 
6.1%
i 261
 
5.2%
a 246
 
4.9%
t 227
 
4.5%
n 213
 
4.3%
h 175
 
3.5%
Other values (39) 1661
33.2%

start_time
Text

MISSING 

Distinct33
Distinct (%)7.1%
Missing11
Missing (%)2.3%
Memory size28.9 KiB
2023-12-09T22:48:39.668716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.96112311
Min length3

Characters and Unicode

Total characters2760
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.0%

Sample

1st row7:45am
2nd row8:00am
3rd row8:20am
4th row8:00am
5th row8:20am
ValueCountFrequency (%)
8:00am 190
40.8%
8:20am 69
 
14.8%
8:10am 54
 
11.6%
8:15am 32
 
6.9%
8:30am 24
 
5.2%
8:05am 14
 
3.0%
8:40am 13
 
2.8%
7:45am 12
 
2.6%
7:30am 6
 
1.3%
7:50am 5
 
1.1%
Other values (24) 47
 
10.1%
2023-12-09T22:48:40.015144image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 578
20.9%
a 461
16.7%
m 461
16.7%
: 456
16.5%
8 425
15.4%
5 89
 
3.2%
1 87
 
3.2%
2 79
 
2.9%
3 40
 
1.4%
4 35
 
1.3%
Other values (6) 49
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1373
49.7%
Lowercase Letter 922
33.4%
Other Punctuation 456
 
16.5%
Uppercase Letter 6
 
0.2%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 578
42.1%
8 425
31.0%
5 89
 
6.5%
1 87
 
6.3%
2 79
 
5.8%
3 40
 
2.9%
4 35
 
2.5%
7 33
 
2.4%
9 7
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
33.3%
B 2
33.3%
D 2
33.3%
Lowercase Letter
ValueCountFrequency (%)
a 461
50.0%
m 461
50.0%
Other Punctuation
ValueCountFrequency (%)
: 456
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1832
66.4%
Latin 928
33.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 578
31.6%
: 456
24.9%
8 425
23.2%
5 89
 
4.9%
1 87
 
4.7%
2 79
 
4.3%
3 40
 
2.2%
4 35
 
1.9%
7 33
 
1.8%
9 7
 
0.4%
Latin
ValueCountFrequency (%)
a 461
49.7%
m 461
49.7%
T 2
 
0.2%
B 2
 
0.2%
D 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 578
20.9%
a 461
16.7%
m 461
16.7%
: 456
16.5%
8 425
15.4%
5 89
 
3.2%
1 87
 
3.2%
2 79
 
2.9%
3 40
 
1.4%
4 35
 
1.3%
Other values (6) 49
 
1.8%

end_time
Text

MISSING 

Distinct63
Distinct (%)13.7%
Missing13
Missing (%)2.7%
Memory size28.8 KiB
2023-12-09T22:48:40.286483image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length6
Mean length5.889370933
Min length3

Characters and Unicode

Total characters2715
Distinct characters28
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)7.2%

Sample

1st row2:40pm
2nd row2:20pm
3rd row2:40pm
4th row2:50pm
5th row2:40pm
ValueCountFrequency (%)
2:20pm 153
32.6%
2:30pm 55
 
11.7%
2:40pm 50
 
10.6%
2:35pm 24
 
5.1%
2:50pm 22
 
4.7%
3:20pm 15
 
3.2%
3pm 12
 
2.6%
2:25pm 11
 
2.3%
4pm 10
 
2.1%
3:05pm 7
 
1.5%
Other values (56) 111
23.6%
2023-12-09T22:48:40.685377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 561
20.7%
p 462
17.0%
m 462
17.0%
: 432
15.9%
0 338
12.4%
3 168
 
6.2%
5 120
 
4.4%
4 83
 
3.1%
1 32
 
1.2%
6 9
 
0.3%
Other values (18) 48
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1326
48.8%
Lowercase Letter 941
34.7%
Other Punctuation 432
 
15.9%
Space Separator 9
 
0.3%
Uppercase Letter 3
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 462
49.1%
m 462
49.1%
a 3
 
0.3%
s 3
 
0.3%
y 2
 
0.2%
d 2
 
0.2%
i 2
 
0.2%
r 2
 
0.2%
o 1
 
0.1%
n 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 561
42.3%
0 338
25.5%
3 168
 
12.7%
5 120
 
9.0%
4 83
 
6.3%
1 32
 
2.4%
6 9
 
0.7%
9 7
 
0.5%
8 4
 
0.3%
7 4
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
F 1
33.3%
M 1
33.3%
V 1
33.3%
Other Punctuation
ValueCountFrequency (%)
: 432
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1771
65.2%
Latin 944
34.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 561
31.7%
: 432
24.4%
0 338
19.1%
3 168
 
9.5%
5 120
 
6.8%
4 83
 
4.7%
1 32
 
1.8%
6 9
 
0.5%
9
 
0.5%
9 7
 
0.4%
Other values (4) 12
 
0.7%
Latin
ValueCountFrequency (%)
p 462
48.9%
m 462
48.9%
a 3
 
0.3%
s 3
 
0.3%
y 2
 
0.2%
d 2
 
0.2%
i 2
 
0.2%
r 2
 
0.2%
F 1
 
0.1%
M 1
 
0.1%
Other values (4) 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 561
20.7%
p 462
17.0%
m 462
17.0%
: 432
15.9%
0 338
12.4%
3 168
 
6.2%
5 120
 
4.4%
4 83
 
3.1%
1 32
 
1.2%
6 9
 
0.3%
Other values (18) 48
 
1.8%

ellprograms
Text

Distinct9
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
2023-12-09T22:48:40.882750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length94
Median length25
Mean length28.06329114
Min length25

Characters and Unicode

Total characters13302
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.1%

Sample

1st rowEnglish as a New Language
2nd rowEnglish as a New Language
3rd rowEnglish as a New Language;Dual Language: Chinese
4th rowEnglish as a New Language;Dual Language: Spanish
5th rowEnglish as a New Language
ValueCountFrequency (%)
language 478
19.1%
english 474
19.0%
as 474
19.0%
a 474
19.0%
new 474
19.0%
language;dual 59
 
2.4%
spanish 49
 
2.0%
chinese 6
 
0.2%
french 2
 
0.1%
arabic 1
 
< 0.1%
Other values (6) 6
 
0.2%
2023-12-09T22:48:41.195565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2139
16.1%
2023
15.2%
g 1548
11.6%
n 1073
8.1%
e 1030
7.7%
s 1008
7.6%
u 602
 
4.5%
l 538
 
4.0%
L 537
 
4.0%
i 535
 
4.0%
Other values (19) 2269
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9541
71.7%
Space Separator 2023
 
15.2%
Uppercase Letter 1612
 
12.1%
Other Punctuation 126
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2139
22.4%
g 1548
16.2%
n 1073
11.2%
e 1030
10.8%
s 1008
10.6%
u 602
 
6.3%
l 538
 
5.6%
i 535
 
5.6%
h 533
 
5.6%
w 474
 
5.0%
Other values (6) 61
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
L 537
33.3%
E 474
29.4%
N 474
29.4%
D 63
 
3.9%
S 49
 
3.0%
C 8
 
0.5%
F 3
 
0.2%
R 2
 
0.1%
A 1
 
0.1%
H 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 63
50.0%
; 63
50.0%
Space Separator
ValueCountFrequency (%)
2023
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11153
83.8%
Common 2149
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2139
19.2%
g 1548
13.9%
n 1073
9.6%
e 1030
9.2%
s 1008
9.0%
u 602
 
5.4%
l 538
 
4.8%
L 537
 
4.8%
i 535
 
4.8%
h 533
 
4.8%
Other values (16) 1610
14.4%
Common
ValueCountFrequency (%)
2023
94.1%
: 63
 
2.9%
; 63
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2139
16.1%
2023
15.2%
g 1548
11.6%
n 1073
8.1%
e 1030
7.7%
s 1008
7.6%
u 602
 
4.5%
l 538
 
4.0%
L 537
 
4.0%
i 535
 
4.0%
Other values (19) 2269
17.1%

other_features
Text

MISSING 

Distinct15
Distinct (%)5.1%
Missing177
Missing (%)37.3%
Memory size31.4 KiB
2023-12-09T22:48:41.392703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length51
Median length38
Mean length31.76094276
Min length7

Characters and Unicode

Total characters9433
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowExtended Day,Summer Session,Weekend Program,Uniform
2nd rowExtended Day,Summer Session,Weekend Program,Uniform
3rd rowExtended Day,Uniform
4th rowExtended Day,Summer Session,Weekend Program
5th rowUniform
ValueCountFrequency (%)
extended 168
20.3%
program,uniform 147
17.8%
session,weekend 132
15.9%
day,summer 115
13.9%
summer 67
 
8.1%
uniform 39
 
4.7%
session,uniform 37
 
4.5%
program 34
 
4.1%
day,weekend 26
 
3.1%
weekend 23
 
2.8%
Other values (3) 40
 
4.8%
2023-12-09T22:48:41.729457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1243
13.2%
m 785
 
8.3%
r 784
 
8.3%
n 771
 
8.2%
o 603
 
6.4%
531
 
5.6%
d 517
 
5.5%
, 474
 
5.0%
i 422
 
4.5%
S 364
 
3.9%
Other values (14) 2939
31.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7126
75.5%
Uppercase Letter 1302
 
13.8%
Space Separator 531
 
5.6%
Other Punctuation 474
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1243
17.4%
m 785
11.0%
r 784
11.0%
n 771
10.8%
o 603
8.5%
d 517
7.3%
i 422
 
5.9%
s 364
 
5.1%
a 349
 
4.9%
f 240
 
3.4%
Other values (6) 1048
14.7%
Uppercase Letter
ValueCountFrequency (%)
S 364
28.0%
U 240
18.4%
W 181
13.9%
P 181
13.9%
D 168
12.9%
E 168
12.9%
Space Separator
ValueCountFrequency (%)
531
100.0%
Other Punctuation
ValueCountFrequency (%)
, 474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8428
89.3%
Common 1005
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1243
14.7%
m 785
 
9.3%
r 784
 
9.3%
n 771
 
9.1%
o 603
 
7.2%
d 517
 
6.1%
i 422
 
5.0%
S 364
 
4.3%
s 364
 
4.3%
a 349
 
4.1%
Other values (12) 2226
26.4%
Common
ValueCountFrequency (%)
531
52.8%
, 474
47.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1243
13.2%
m 785
 
8.3%
r 784
 
8.3%
n 771
 
8.2%
o 603
 
6.4%
531
 
5.6%
d 517
 
5.5%
, 474
 
5.0%
i 422
 
4.5%
S 364
 
3.9%
Other values (14) 2939
31.2%

languageclasses
Text

MISSING 

Distinct37
Distinct (%)10.0%
Missing105
Missing (%)22.2%
Memory size27.5 KiB
2023-12-09T22:48:41.970094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length7
Mean length9.872628726
Min length5

Characters and Unicode

Total characters3643
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)6.0%

Sample

1st rowSpanish
2nd rowMandarin
3rd rowSpanish
4th rowMandarin
5th rowOther Language
ValueCountFrequency (%)
spanish 248
57.7%
language 38
 
8.8%
other 34
 
7.9%
french 13
 
3.0%
language;spanish 11
 
2.6%
mandarin 10
 
2.3%
french;spanish 9
 
2.1%
spanish;other 8
 
1.9%
sign 7
 
1.6%
spanish;italian 6
 
1.4%
Other values (28) 46
 
10.7%
2023-12-09T22:48:42.357158image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 524
14.4%
n 487
13.4%
h 383
10.5%
i 373
10.2%
S 312
8.6%
s 308
8.5%
p 306
8.4%
e 149
 
4.1%
r 116
 
3.2%
g 115
 
3.2%
Other values (21) 570
15.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2988
82.0%
Uppercase Letter 512
 
14.1%
Other Punctuation 82
 
2.3%
Space Separator 61
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 524
17.5%
n 487
16.3%
h 383
12.8%
i 373
12.5%
s 308
10.3%
p 306
10.2%
e 149
 
5.0%
r 116
 
3.9%
g 115
 
3.8%
t 74
 
2.5%
Other values (8) 153
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
S 312
60.9%
L 62
 
12.1%
O 47
 
9.2%
F 31
 
6.1%
M 24
 
4.7%
I 19
 
3.7%
A 9
 
1.8%
K 4
 
0.8%
G 2
 
0.4%
J 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
; 82
100.0%
Space Separator
ValueCountFrequency (%)
61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3500
96.1%
Common 143
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 524
15.0%
n 487
13.9%
h 383
10.9%
i 373
10.7%
S 312
8.9%
s 308
8.8%
p 306
8.7%
e 149
 
4.3%
r 116
 
3.3%
g 115
 
3.3%
Other values (19) 427
12.2%
Common
ValueCountFrequency (%)
; 82
57.3%
61
42.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3643
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 524
14.4%
n 487
13.4%
h 383
10.5%
i 373
10.2%
S 312
8.6%
s 308
8.5%
p 306
8.4%
e 149
 
4.1%
r 116
 
3.2%
g 115
 
3.2%
Other values (21) 570
15.6%

acceleratedclasses
Text

MISSING 

Distinct56
Distinct (%)14.5%
Missing88
Missing (%)18.6%
Memory size35.7 KiB
2023-12-09T22:48:42.567599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length68
Mean length29.98186528
Min length7

Characters and Unicode

Total characters11573
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)6.7%

Sample

1st rowAlgebra I,Living Environment
2nd rowAlgebra I,Living Environment
3rd rowAlgebra I
4th rowAlgebra I
5th rowChinese,Spanish,US History,Algebra I,Geometry,Algebra II,Living Environment
ValueCountFrequency (%)
environment 262
22.0%
i,living 224
18.8%
algebra 197
16.6%
history,algebra 106
8.9%
i 73
 
6.1%
us 63
 
5.3%
i,earth 53
 
4.5%
spanish,algebra 41
 
3.4%
science 40
 
3.4%
spanish,us 21
 
1.8%
Other values (35) 110
9.2%
2023-12-09T22:48:42.929591image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1250
 
10.8%
i 1099
 
9.5%
r 820
 
7.1%
804
 
6.9%
e 785
 
6.8%
g 657
 
5.7%
, 561
 
4.8%
a 530
 
4.6%
v 530
 
4.6%
t 457
 
3.9%
Other values (20) 4080
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8345
72.1%
Uppercase Letter 1863
 
16.1%
Space Separator 804
 
6.9%
Other Punctuation 561
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1250
15.0%
i 1099
13.2%
r 820
9.8%
e 785
9.4%
g 657
7.9%
a 530
 
6.4%
v 530
 
6.4%
t 457
 
5.5%
l 407
 
4.9%
o 392
 
4.7%
Other values (7) 1418
17.0%
Uppercase Letter
ValueCountFrequency (%)
I 374
20.1%
A 365
19.6%
E 353
18.9%
L 266
14.3%
S 257
13.8%
H 113
 
6.1%
U 108
 
5.8%
G 14
 
0.8%
C 7
 
0.4%
F 4
 
0.2%
Space Separator
ValueCountFrequency (%)
804
100.0%
Other Punctuation
ValueCountFrequency (%)
, 561
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10208
88.2%
Common 1365
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1250
 
12.2%
i 1099
 
10.8%
r 820
 
8.0%
e 785
 
7.7%
g 657
 
6.4%
a 530
 
5.2%
v 530
 
5.2%
t 457
 
4.5%
l 407
 
4.0%
o 392
 
3.8%
Other values (18) 3281
32.1%
Common
ValueCountFrequency (%)
804
58.9%
, 561
41.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1250
 
10.8%
i 1099
 
9.5%
r 820
 
7.1%
804
 
6.9%
e 785
 
6.8%
g 657
 
5.7%
, 561
 
4.8%
a 530
 
4.6%
v 530
 
4.6%
t 457
 
3.9%
Other values (20) 4080
35.3%

electiveclasses
Text

MISSING 

Distinct355
Distinct (%)99.7%
Missing118
Missing (%)24.9%
Memory size115.6 KiB
2023-12-09T22:48:43.247286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length863
Median length333.5
Mean length264.6797753
Min length1

Characters and Unicode

Total characters94226
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique354 ?
Unique (%)99.4%

Sample

1st rowAdvisory, Math, Music, Peer Mediation, Saturday Academy, Science, Spanish, Yearbook
2nd rowAdvisory, Art, Dance, Fitness, Foreign Language, Health, National Junior Honor Society, Peer Mediation, Physical Education, Spanish, Student Council, Urban Advantage, Visual Arts
3rd rowAdvisory, Algebra I, Art, Chorus, Computer Science, Dance, Debate, Fine Arts, Foreign Language, Health, Jazz Band, Living Environment, Math, Mindfulness, Physical Education, Regents Living Environment, Saturday Academy, Studio Art, Urban Advantage, Visual Arts, Yearbook
4th rowAdvisory, Book Club, Fashion, Living Environment, Physical Education, Regents Living Environment, Science, Specialized High School Test Preparation, Student Council, Technology, Yearbook, CC Algebra Regents
5th rowAdvisory, Algebra I, Art, Book Club, Chess, Creative Writing, Fine Arts, Fitness, Foreign Language, Health, Living Environment, Math, Mindfulness, Regents Living Environment, Spanish, Specialized High School Test Preparation, Student Council, Studio Art, Technology, US History, Visual Arts, Vocal Music, Yearbook, Yoga
ValueCountFrequency (%)
arts 426
 
3.6%
art 337
 
2.9%
living 330
 
2.8%
environment 329
 
2.8%
science 277
 
2.3%
band 262
 
2.2%
algebra 258
 
2.2%
i 257
 
2.2%
music 253
 
2.1%
education 239
 
2.0%
Other values (339) 8846
74.9%
2023-12-09T22:48:43.735285image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11458
 
12.2%
, 7052
 
7.5%
e 6404
 
6.8%
i 6210
 
6.6%
n 5913
 
6.3%
a 5908
 
6.3%
o 4950
 
5.3%
r 4935
 
5.2%
t 4664
 
4.9%
s 3386
 
3.6%
Other values (56) 33346
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 63000
66.9%
Uppercase Letter 12664
 
13.4%
Space Separator 11458
 
12.2%
Other Punctuation 7068
 
7.5%
Dash Punctuation 14
 
< 0.1%
Decimal Number 10
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6404
10.2%
i 6210
9.9%
n 5913
 
9.4%
a 5908
 
9.4%
o 4950
 
7.9%
r 4935
 
7.8%
t 4664
 
7.4%
s 3386
 
5.4%
c 3048
 
4.8%
g 2637
 
4.2%
Other values (16) 14945
23.7%
Uppercase Letter
ValueCountFrequency (%)
S 1587
12.5%
A 1561
12.3%
C 1090
 
8.6%
M 975
 
7.7%
E 904
 
7.1%
T 733
 
5.8%
L 730
 
5.8%
P 705
 
5.6%
D 618
 
4.9%
F 532
 
4.2%
Other values (14) 3229
25.5%
Other Punctuation
ValueCountFrequency (%)
, 7052
99.8%
. 5
 
0.1%
: 4
 
0.1%
& 3
 
< 0.1%
/ 3
 
< 0.1%
' 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
6 3
30.0%
3 3
30.0%
7 1
 
10.0%
5 1
 
10.0%
4 1
 
10.0%
8 1
 
10.0%
Space Separator
ValueCountFrequency (%)
11458
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 75664
80.3%
Common 18562
 
19.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6404
 
8.5%
i 6210
 
8.2%
n 5913
 
7.8%
a 5908
 
7.8%
o 4950
 
6.5%
r 4935
 
6.5%
t 4664
 
6.2%
s 3386
 
4.5%
c 3048
 
4.0%
g 2637
 
3.5%
Other values (40) 27609
36.5%
Common
ValueCountFrequency (%)
11458
61.7%
, 7052
38.0%
- 14
 
0.1%
) 6
 
< 0.1%
( 6
 
< 0.1%
. 5
 
< 0.1%
: 4
 
< 0.1%
6 3
 
< 0.1%
& 3
 
< 0.1%
3 3
 
< 0.1%
Other values (6) 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11458
 
12.2%
, 7052
 
7.5%
e 6404
 
6.8%
i 6210
 
6.6%
n 5913
 
6.3%
a 5908
 
6.3%
o 4950
 
5.3%
r 4935
 
5.2%
t 4664
 
4.9%
s 3386
 
3.6%
Other values (56) 33346
35.4%

activities_description
Text

MISSING 

Distinct355
Distinct (%)100.0%
Missing119
Missing (%)25.1%
Memory size95.2 KiB
2023-12-09T22:48:45.144967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length600
Median length266
Mean length206.4112676
Min length4

Characters and Unicode

Total characters73276
Distinct characters69
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique355 ?
Unique (%)100.0%

Sample

1st rowTalent Show, Yearbook, Cheerleaders
2nd rowArt, Dance, Leadership, Music, Restorative Circles, Saturday Academy, Spelling Bee, Technology, Tutoring, Visual Arts, Yearbook, Yoga
3rd rowSaturday Academy, Student Council, Technology, Yearbook
4th rowArt, Book Club, Chess, Gardening, Homework Help, Music, Peer Mediation, Restorative Circles, Student Council, Technology, Tutoring, Visual Arts, Yearbook, Yoga
5th rowArt, Band, Book Club, Chess, Coding, Comic Book Club, Cooking, Creative Writing, Dance, Debate, Drama, Fitness, Gardening, Green Team, Homework Help, Leadership, Math Team, Music, National Junior Honor Society, Peer Mediation, Photography, Robotics, Rock Band, Service Learning, STEM, Student Council, Talent Show, Technology, Tutoring, Video Game Club, Visual Arts, Yoga, Dungeons and Dragons Club, Gay-straight Alliance, Activism Club, Brotherhood, Sisterhood
ValueCountFrequency (%)
club 337
 
3.6%
art 282
 
3.0%
team 263
 
2.8%
student 260
 
2.8%
theater 248
 
2.6%
council 246
 
2.6%
yearbook 234
 
2.5%
robotics 227
 
2.4%
dance 221
 
2.3%
arts 202
 
2.1%
Other values (434) 6918
73.3%
2023-12-09T22:48:45.689516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9085
 
12.4%
e 6324
 
8.6%
, 5713
 
7.8%
o 4893
 
6.7%
a 4289
 
5.9%
i 3898
 
5.3%
r 3760
 
5.1%
t 3661
 
5.0%
n 3398
 
4.6%
s 2375
 
3.2%
Other values (59) 25880
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 48496
66.2%
Uppercase Letter 9894
 
13.5%
Space Separator 9085
 
12.4%
Other Punctuation 5740
 
7.8%
Dash Punctuation 21
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Close Punctuation 15
 
< 0.1%
Decimal Number 10
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6324
13.0%
o 4893
10.1%
a 4289
 
8.8%
i 3898
 
8.0%
r 3760
 
7.8%
t 3661
 
7.5%
n 3398
 
7.0%
s 2375
 
4.9%
l 2213
 
4.6%
c 2161
 
4.5%
Other values (16) 11524
23.8%
Uppercase Letter
ValueCountFrequency (%)
C 1491
15.1%
S 1360
13.7%
T 1140
11.5%
A 728
 
7.4%
M 711
 
7.2%
D 541
 
5.5%
H 523
 
5.3%
B 485
 
4.9%
R 445
 
4.5%
L 378
 
3.8%
Other values (16) 2092
21.1%
Other Punctuation
ValueCountFrequency (%)
, 5713
99.5%
. 7
 
0.1%
/ 6
 
0.1%
: 5
 
0.1%
" 4
 
0.1%
& 3
 
0.1%
' 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
4 2
20.0%
0 2
20.0%
2 2
20.0%
5 2
20.0%
8 1
10.0%
3 1
10.0%
Space Separator
ValueCountFrequency (%)
9085
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 58390
79.7%
Common 14886
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6324
 
10.8%
o 4893
 
8.4%
a 4289
 
7.3%
i 3898
 
6.7%
r 3760
 
6.4%
t 3661
 
6.3%
n 3398
 
5.8%
s 2375
 
4.1%
l 2213
 
3.8%
c 2161
 
3.7%
Other values (42) 21418
36.7%
Common
ValueCountFrequency (%)
9085
61.0%
, 5713
38.4%
- 21
 
0.1%
( 15
 
0.1%
) 15
 
0.1%
. 7
 
< 0.1%
/ 6
 
< 0.1%
: 5
 
< 0.1%
" 4
 
< 0.1%
& 3
 
< 0.1%
Other values (7) 12
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9085
 
12.4%
e 6324
 
8.6%
, 5713
 
7.8%
o 4893
 
6.7%
a 4289
 
5.9%
i 3898
 
5.3%
r 3760
 
5.1%
t 3661
 
5.0%
n 3398
 
4.6%
s 2375
 
3.2%
Other values (59) 25880
35.3%

othersports
Text

MISSING 

Distinct284
Distinct (%)80.5%
Missing121
Missing (%)25.5%
Memory size42.6 KiB
2023-12-09T22:48:45.940719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length244
Median length123
Mean length55.3796034
Min length4

Characters and Unicode

Total characters19549
Distinct characters55
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)72.5%

Sample

1st rowBasketball, Fitness Club, Flag Football
2nd rowSports are only by champs
3rd rowRunning Club, Volleyball
4th rowBadminton, Basketball, Flag Football
5th rowFitness Club, Flag Football, Running Club, Soccer, Softball, Yoga
ValueCountFrequency (%)
basketball 277
 
11.5%
soccer 156
 
6.5%
club 156
 
6.5%
football 131
 
5.5%
volleyball 130
 
5.4%
dance 129
 
5.4%
flag 117
 
4.9%
and 110
 
4.6%
field 106
 
4.4%
track 105
 
4.4%
Other values (101) 986
41.0%
2023-12-09T22:48:46.355892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2268
 
11.6%
2051
 
10.5%
a 1822
 
9.3%
e 1542
 
7.9%
, 1374
 
7.0%
n 959
 
4.9%
b 926
 
4.7%
o 827
 
4.2%
t 786
 
4.0%
s 772
 
3.9%
Other values (45) 6222
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13843
70.8%
Uppercase Letter 2271
 
11.6%
Space Separator 2051
 
10.5%
Other Punctuation 1378
 
7.0%
Dash Punctuation 4
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 454
20.0%
B 399
17.6%
C 338
14.9%
S 279
12.3%
T 186
8.2%
D 161
 
7.1%
V 135
 
5.9%
R 95
 
4.2%
Y 45
 
2.0%
A 38
 
1.7%
Other values (14) 141
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
l 2268
16.4%
a 1822
13.2%
e 1542
11.1%
n 959
 
6.9%
b 926
 
6.7%
o 827
 
6.0%
t 786
 
5.7%
s 772
 
5.6%
c 629
 
4.5%
i 605
 
4.4%
Other values (13) 2707
19.6%
Other Punctuation
ValueCountFrequency (%)
, 1374
99.7%
/ 2
 
0.1%
. 1
 
0.1%
& 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
2051
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16114
82.4%
Common 3435
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 2268
14.1%
a 1822
 
11.3%
e 1542
 
9.6%
n 959
 
6.0%
b 926
 
5.7%
o 827
 
5.1%
t 786
 
4.9%
s 772
 
4.8%
c 629
 
3.9%
i 605
 
3.8%
Other values (37) 4978
30.9%
Common
ValueCountFrequency (%)
2051
59.7%
, 1374
40.0%
- 4
 
0.1%
/ 2
 
0.1%
. 1
 
< 0.1%
2 1
 
< 0.1%
6 1
 
< 0.1%
& 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 2268
 
11.6%
2051
 
10.5%
a 1822
 
9.3%
e 1542
 
7.9%
, 1374
 
7.0%
n 959
 
4.9%
b 926
 
4.7%
o 827
 
4.2%
t 786
 
4.0%
s 772
 
3.9%
Other values (45) 6222
31.8%

postcode
Text

Distinct150
Distinct (%)31.8%
Missing2
Missing (%)0.4%
Memory size28.8 KiB
2023-12-09T22:48:46.744379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2360
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)8.9%

Sample

1st row10009
2nd row10002
3rd row10002
4th row10002
5th row10002
ValueCountFrequency (%)
10456 14
 
3.0%
10457 13
 
2.8%
11212 10
 
2.1%
10029 10
 
2.1%
10453 10
 
2.1%
11204 9
 
1.9%
10027 9
 
1.9%
11207 9
 
1.9%
10467 9
 
1.9%
10460 8
 
1.7%
Other values (140) 371
78.6%
2023-12-09T22:48:47.252101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 832
35.3%
0 432
18.3%
2 277
 
11.7%
4 215
 
9.1%
3 192
 
8.1%
5 122
 
5.2%
6 118
 
5.0%
7 80
 
3.4%
9 51
 
2.2%
8 41
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2360
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 832
35.3%
0 432
18.3%
2 277
 
11.7%
4 215
 
9.1%
3 192
 
8.1%
5 122
 
5.2%
6 118
 
5.0%
7 80
 
3.4%
9 51
 
2.2%
8 41
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 832
35.3%
0 432
18.3%
2 277
 
11.7%
4 215
 
9.1%
3 192
 
8.1%
5 122
 
5.2%
6 118
 
5.0%
7 80
 
3.4%
9 51
 
2.2%
8 41
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 832
35.3%
0 432
18.3%
2 277
 
11.7%
4 215
 
9.1%
3 192
 
8.1%
5 122
 
5.2%
6 118
 
5.0%
7 80
 
3.4%
9 51
 
2.2%
8 41
 
1.7%

borough
Text

Distinct5
Distinct (%)1.1%
Missing2
Missing (%)0.4%
Memory size29.7 KiB
2023-12-09T22:48:47.440697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.048728814
Min length5

Characters and Unicode

Total characters3327
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMANHATTAN
2nd rowMANHATTAN
3rd rowMANHATTAN
4th rowMANHATTAN
5th rowMANHATTAN
ValueCountFrequency (%)
brooklyn 142
29.2%
bronx 116
23.8%
queens 105
21.6%
manhattan 94
19.3%
staten 15
 
3.1%
is 15
 
3.1%
2023-12-09T22:48:47.746958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 566
17.0%
O 400
12.0%
A 297
8.9%
B 258
 
7.8%
R 258
 
7.8%
E 225
 
6.8%
T 218
 
6.6%
K 142
 
4.3%
L 142
 
4.3%
Y 142
 
4.3%
Other values (8) 679
20.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3312
99.5%
Space Separator 15
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 566
17.1%
O 400
12.1%
A 297
9.0%
B 258
 
7.8%
R 258
 
7.8%
E 225
 
6.8%
T 218
 
6.6%
K 142
 
4.3%
L 142
 
4.3%
Y 142
 
4.3%
Other values (7) 664
20.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3312
99.5%
Common 15
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 566
17.1%
O 400
12.1%
A 297
9.0%
B 258
 
7.8%
R 258
 
7.8%
E 225
 
6.8%
T 218
 
6.6%
K 142
 
4.3%
L 142
 
4.3%
Y 142
 
4.3%
Other values (7) 664
20.0%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 566
17.0%
O 400
12.0%
A 297
8.9%
B 258
 
7.8%
R 258
 
7.8%
E 225
 
6.8%
T 218
 
6.6%
K 142
 
4.3%
L 142
 
4.3%
Y 142
 
4.3%
Other values (8) 679
20.4%

latitude
Text

Distinct413
Distinct (%)87.5%
Missing2
Missing (%)0.4%
Memory size30.5 KiB
2023-12-09T22:48:48.113946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.862288136
Min length7

Characters and Unicode

Total characters4183
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)76.3%

Sample

1st row40.726473
2nd row40.71925
3rd row40.711549
4th row40.719598
5th row40.713684
ValueCountFrequency (%)
40.791709 3
 
0.6%
40.827941 3
 
0.6%
40.862109 3
 
0.6%
40.780822 3
 
0.6%
40.884953 3
 
0.6%
40.69719 3
 
0.6%
40.675771 2
 
0.4%
40.843546 2
 
0.4%
40.818874 2
 
0.4%
40.651977 2
 
0.4%
Other values (403) 446
94.5%
2023-12-09T22:48:48.612009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 713
17.0%
0 665
15.9%
. 472
11.3%
8 388
9.3%
6 382
9.1%
7 379
9.1%
5 286
6.8%
3 238
 
5.7%
9 226
 
5.4%
2 222
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3711
88.7%
Other Punctuation 472
 
11.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 713
19.2%
0 665
17.9%
8 388
10.5%
6 382
10.3%
7 379
10.2%
5 286
7.7%
3 238
 
6.4%
9 226
 
6.1%
2 222
 
6.0%
1 212
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 472
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4183
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 713
17.0%
0 665
15.9%
. 472
11.3%
8 388
9.3%
6 382
9.1%
7 379
9.1%
5 286
6.8%
3 238
 
5.7%
9 226
 
5.4%
2 222
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4183
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 713
17.0%
0 665
15.9%
. 472
11.3%
8 388
9.3%
6 382
9.1%
7 379
9.1%
5 286
6.8%
3 238
 
5.7%
9 226
 
5.4%
2 222
 
5.3%

longitude
Text

Distinct413
Distinct (%)87.5%
Missing2
Missing (%)0.4%
Memory size31.0 KiB
2023-12-09T22:48:48.986388image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.88559322
Min length7

Characters and Unicode

Total characters4666
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)76.3%

Sample

1st row-73.975181
2nd row-73.983056
3rd row-73.986542
4th row-73.977904
5th row-73.986336
ValueCountFrequency (%)
73.914374 3
 
0.6%
73.970802 3
 
0.6%
73.864577 3
 
0.6%
73.787192 3
 
0.6%
73.840524 3
 
0.6%
73.976855 3
 
0.6%
73.758784 2
 
0.4%
73.860904 2
 
0.4%
73.896703 2
 
0.4%
73.916077 2
 
0.4%
Other values (403) 446
94.5%
2023-12-09T22:48:49.501909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 781
16.7%
3 657
14.1%
9 487
10.4%
- 472
10.1%
. 472
10.1%
8 363
7.8%
4 263
 
5.6%
1 261
 
5.6%
5 234
 
5.0%
2 232
 
5.0%
Other values (2) 444
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3722
79.8%
Dash Punctuation 472
 
10.1%
Other Punctuation 472
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 781
21.0%
3 657
17.7%
9 487
13.1%
8 363
9.8%
4 263
 
7.1%
1 261
 
7.0%
5 234
 
6.3%
2 232
 
6.2%
6 223
 
6.0%
0 221
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 472
100.0%
Other Punctuation
ValueCountFrequency (%)
. 472
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4666
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 781
16.7%
3 657
14.1%
9 487
10.4%
- 472
10.1%
. 472
10.1%
8 363
7.8%
4 263
 
5.6%
1 261
 
5.6%
5 234
 
5.0%
2 232
 
5.0%
Other values (2) 444
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 781
16.7%
3 657
14.1%
9 487
10.4%
- 472
10.1%
. 472
10.1%
8 363
7.8%
4 263
 
5.6%
1 261
 
5.6%
5 234
 
5.0%
2 232
 
5.0%
Other values (2) 444
9.5%

community_board
Text

Distinct59
Distinct (%)12.5%
Missing2
Missing (%)0.4%
Memory size27.8 KiB
2023-12-09T22:48:49.795706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1416
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row103
2nd row103
3rd row103
4th row103
5th row103
ValueCountFrequency (%)
112 16
 
3.4%
305 16
 
3.4%
412 14
 
3.0%
414 14
 
3.0%
204 14
 
3.0%
316 14
 
3.0%
206 14
 
3.0%
107 14
 
3.0%
111 14
 
3.0%
203 13
 
2.8%
Other values (49) 329
69.7%
2023-12-09T22:48:50.197388image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 352
24.9%
0 319
22.5%
3 198
14.0%
2 187
13.2%
4 154
10.9%
5 61
 
4.3%
7 45
 
3.2%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1416
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 352
24.9%
0 319
22.5%
3 198
14.0%
2 187
13.2%
4 154
10.9%
5 61
 
4.3%
7 45
 
3.2%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1416
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 352
24.9%
0 319
22.5%
3 198
14.0%
2 187
13.2%
4 154
10.9%
5 61
 
4.3%
7 45
 
3.2%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1416
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 352
24.9%
0 319
22.5%
3 198
14.0%
2 187
13.2%
4 154
10.9%
5 61
 
4.3%
7 45
 
3.2%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

council_district
Text

Distinct51
Distinct (%)10.8%
Missing2
Missing (%)0.4%
Memory size27.3 KiB
2023-12-09T22:48:50.460938image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.819915254
Min length1

Characters and Unicode

Total characters859
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row1
ValueCountFrequency (%)
16 20
 
4.2%
17 20
 
4.2%
8 20
 
4.2%
37 15
 
3.2%
42 15
 
3.2%
10 15
 
3.2%
31 15
 
3.2%
14 14
 
3.0%
13 13
 
2.8%
15 13
 
2.8%
Other values (41) 312
66.1%
2023-12-09T22:48:50.840651image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 191
22.2%
3 140
16.3%
4 128
14.9%
2 116
13.5%
7 64
 
7.5%
6 54
 
6.3%
8 51
 
5.9%
5 46
 
5.4%
0 36
 
4.2%
9 33
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 859
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 191
22.2%
3 140
16.3%
4 128
14.9%
2 116
13.5%
7 64
 
7.5%
6 54
 
6.3%
8 51
 
5.9%
5 46
 
5.4%
0 36
 
4.2%
9 33
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 859
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 191
22.2%
3 140
16.3%
4 128
14.9%
2 116
13.5%
7 64
 
7.5%
6 54
 
6.3%
8 51
 
5.9%
5 46
 
5.4%
0 36
 
4.2%
9 33
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 859
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 191
22.2%
3 140
16.3%
4 128
14.9%
2 116
13.5%
7 64
 
7.5%
6 54
 
6.3%
8 51
 
5.9%
5 46
 
5.4%
0 36
 
4.2%
9 33
 
3.8%

census_tract
Text

Distinct339
Distinct (%)71.8%
Missing2
Missing (%)0.4%
Memory size28.0 KiB
2023-12-09T22:48:51.345533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.266949153
Min length1

Characters and Unicode

Total characters1542
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)50.4%

Sample

1st row28
2nd row2201
3rd row201
4th row20
5th row201
ValueCountFrequency (%)
330 5
 
1.1%
409 4
 
0.8%
291 4
 
0.8%
177 4
 
0.8%
73 4
 
0.8%
161 4
 
0.8%
69 4
 
0.8%
1170 3
 
0.6%
64 3
 
0.6%
18302 3
 
0.6%
Other values (329) 434
91.9%
2023-12-09T22:48:51.985196image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 258
16.7%
2 216
14.0%
0 180
11.7%
3 175
11.3%
4 151
9.8%
9 122
7.9%
7 117
7.6%
8 110
7.1%
5 109
7.1%
6 104
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1542
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 258
16.7%
2 216
14.0%
0 180
11.7%
3 175
11.3%
4 151
9.8%
9 122
7.9%
7 117
7.6%
8 110
7.1%
5 109
7.1%
6 104
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1542
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 258
16.7%
2 216
14.0%
0 180
11.7%
3 175
11.3%
4 151
9.8%
9 122
7.9%
7 117
7.6%
8 110
7.1%
5 109
7.1%
6 104
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1542
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 258
16.7%
2 216
14.0%
0 180
11.7%
3 175
11.3%
4 151
9.8%
9 122
7.9%
7 117
7.6%
8 110
7.1%
5 109
7.1%
6 104
6.7%

bin
Text

Distinct412
Distinct (%)87.3%
Missing2
Missing (%)0.4%
Memory size29.7 KiB
2023-12-09T22:48:52.422526image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3304
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique358 ?
Unique (%)75.8%

Sample

1st row1004564
2nd row1004091
3rd row1003143
4th row1004349
5th row1003223
ValueCountFrequency (%)
2066190 3
 
0.6%
1032522 3
 
0.6%
2051313 3
 
0.6%
2097111 3
 
0.6%
1030178 3
 
0.6%
4216655 3
 
0.6%
1055204 2
 
0.4%
2005660 2
 
0.4%
2018046 2
 
0.4%
2094582 2
 
0.4%
Other values (402) 446
94.5%
2023-12-09T22:48:52.965275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 578
17.5%
1 429
13.0%
3 411
12.4%
4 380
11.5%
2 360
10.9%
8 245
7.4%
5 240
7.3%
6 223
 
6.7%
7 220
 
6.7%
9 218
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3304
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 578
17.5%
1 429
13.0%
3 411
12.4%
4 380
11.5%
2 360
10.9%
8 245
7.4%
5 240
7.3%
6 223
 
6.7%
7 220
 
6.7%
9 218
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 578
17.5%
1 429
13.0%
3 411
12.4%
4 380
11.5%
2 360
10.9%
8 245
7.4%
5 240
7.3%
6 223
 
6.7%
7 220
 
6.7%
9 218
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 578
17.5%
1 429
13.0%
3 411
12.4%
4 380
11.5%
2 360
10.9%
8 245
7.4%
5 240
7.3%
6 223
 
6.7%
7 220
 
6.7%
9 218
 
6.6%

bbl
Text

Distinct407
Distinct (%)86.2%
Missing2
Missing (%)0.4%
Memory size31.1 KiB
2023-12-09T22:48:53.294874image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4720
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique348 ?
Unique (%)73.7%

Sample

1st row1003810038
2nd row1003440001
3rd row1002450007
4th row1003560100
5th row1002690041
ValueCountFrequency (%)
4101780001 3
 
0.6%
1012230005 3
 
0.6%
2044320001 3
 
0.6%
2049350001 3
 
0.6%
1011480014 3
 
0.6%
2024240001 3
 
0.6%
2026160001 2
 
0.4%
4052610001 2
 
0.4%
2024460043 2
 
0.4%
2026550030 2
 
0.4%
Other values (397) 446
94.5%
2023-12-09T22:48:53.742701image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1821
38.6%
1 685
 
14.5%
3 449
 
9.5%
2 444
 
9.4%
4 371
 
7.9%
5 242
 
5.1%
6 207
 
4.4%
8 184
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4720
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1821
38.6%
1 685
 
14.5%
3 449
 
9.5%
2 444
 
9.4%
4 371
 
7.9%
5 242
 
5.1%
6 207
 
4.4%
8 184
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1821
38.6%
1 685
 
14.5%
3 449
 
9.5%
2 444
 
9.4%
4 371
 
7.9%
5 242
 
5.1%
6 207
 
4.4%
8 184
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1821
38.6%
1 685
 
14.5%
3 449
 
9.5%
2 444
 
9.4%
4 371
 
7.9%
5 242
 
5.1%
6 207
 
4.4%
8 184
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

nta
Text

Distinct164
Distinct (%)34.7%
Missing2
Missing (%)0.4%
Memory size35.6 KiB
2023-12-09T22:48:54.050089image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length56
Median length39
Mean length19.78601695
Min length6

Characters and Unicode

Total characters9339
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)10.0%

Sample

1st rowLower East Side
2nd rowLower East Side
3rd rowLower East Side
4th rowLower East Side
5th rowLower East Side
ValueCountFrequency (%)
east 69
 
6.3%
heights 43
 
3.9%
park 39
 
3.6%
south 37
 
3.4%
north 36
 
3.3%
village 26
 
2.4%
harlem 23
 
2.1%
west 22
 
2.0%
side 19
 
1.7%
hill 17
 
1.6%
Other values (224) 758
69.6%
2023-12-09T22:48:54.518604image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 804
 
8.6%
a 680
 
7.3%
r 622
 
6.7%
o 621
 
6.6%
617
 
6.6%
t 614
 
6.6%
n 534
 
5.7%
s 502
 
5.4%
l 479
 
5.1%
i 457
 
4.9%
Other values (45) 3409
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7076
75.8%
Uppercase Letter 1367
 
14.6%
Space Separator 617
 
6.6%
Dash Punctuation 264
 
2.8%
Other Punctuation 7
 
0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 804
11.4%
a 680
9.6%
r 622
8.8%
o 621
8.8%
t 614
8.7%
n 534
 
7.5%
s 502
 
7.1%
l 479
 
6.8%
i 457
 
6.5%
h 292
 
4.1%
Other values (15) 1471
20.8%
Uppercase Letter
ValueCountFrequency (%)
H 190
13.9%
B 140
10.2%
S 132
9.7%
C 122
 
8.9%
P 100
 
7.3%
E 94
 
6.9%
M 88
 
6.4%
N 67
 
4.9%
W 56
 
4.1%
G 49
 
3.6%
Other values (14) 329
24.1%
Other Punctuation
ValueCountFrequency (%)
. 5
71.4%
' 2
 
28.6%
Space Separator
ValueCountFrequency (%)
617
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8443
90.4%
Common 896
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 804
 
9.5%
a 680
 
8.1%
r 622
 
7.4%
o 621
 
7.4%
t 614
 
7.3%
n 534
 
6.3%
s 502
 
5.9%
l 479
 
5.7%
i 457
 
5.4%
h 292
 
3.5%
Other values (39) 2838
33.6%
Common
ValueCountFrequency (%)
617
68.9%
- 264
29.5%
. 5
 
0.6%
( 4
 
0.4%
) 4
 
0.4%
' 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 804
 
8.6%
a 680
 
7.3%
r 622
 
6.7%
o 621
 
6.6%
617
 
6.6%
t 614
 
6.6%
n 534
 
5.7%
s 502
 
5.4%
l 479
 
5.1%
i 457
 
4.9%
Other values (45) 3409
36.5%